The Human Resources built-in sample contains a dashboard, report, and dataset for a human resources department. In this sample, the human resources department has the same reporting model across different companies, even when they differ by industry or size. This sample looks at new hires, active employees, and employees who have left. It strives to uncover any trends in the hiring strategy. Our main objectives are to understand:
Who we hire
Biases in our hiring strategy
Trends in voluntary separations
This sample is part of a series that shows how you can use Power BI with business-oriented data, reports, and dashboards. It was created by obviEnce with real data, which has been anonymized. The data is available in several formats: built-in sample in the Power BI service, .pbix Power BI Desktop file, or Excel workbook. See Samples for Power BI.
This tutorial explores the Human Resources built-in sample in the Power BI service. Because the report experience is similar in Power BI Desktop and in the service, you can also follow along by using the sample .pbix file in Power BI Desktop.
You don’t need a Power BI license to explore the samples in Power BI Desktop. If you don’t have a Power BI Pro or Premium Per User (PPU) license, you can save the sample to your My Workspace in the Power BI service.
Open the Power BI service (app.powerbi.com), sign in, and open the workspace where you want to save the sample.If you don’t have a Power BI Pro or Premium Per User (PPU) license, you can save the sample to your My Workspace.
In the bottom-left corner, select Get data.
On the Get Data page that appears, select Samples.
Select Human Resources Sample, then choose Connect.
Power BI imports the built-in sample and then adds a new dashboard, report, and dataset to your current workspace.
Get the .pbix file for this sample
Alternatively, you can download the Human Resources sample as a .pbix file, which is designed for use with Power BI Desktop.
Get the Excel workbook for this sample
If you want to view the data source for this sample, it’s also available as an Excel workbook. The workbook contains Power View sheets that you can view and modify. To see the raw data, enable the Data Analysis add-ins, and then select Power Pivot > Manage. To enable the Power View and Power Pivot add-ins, see Explore the Excel samples in Excel for details.
New hires
Let’s explore new hires first.
In your workspace, select the Dashboards tab, and open the Human Resources Sample dashboard.
On the dashboard, select the New Hire Count, New Hires Same Period Last Year, Actives YoY % Change By Month tile.
The Human Resources Sample report opens to the New Hires page.
Look at these items of interest:
The New Hire Count, New Hires SPLY and Actives YoY % Change by Month combo chart shows we hired more people every month this year compared to last year. Significantly more people in some months.
In the combo chart New Hire Count and Active Employee Count by Region and Ethnicity, notice we’re hiring fewer people in the East region.
The New Hires YoY Var by Age Group waterfall chart shows we’re hiring mainly younger people. This trend may be due to the mostly part-time nature of the jobs.
The New Hire Count by Gender pie chart shows a roughly even split.
Can you find more insights? For example, a region where the gender split is not even.
Select different age groups and genders in the charts to explore the relationships between age, gender, region, and ethnicity group.
Select Human Resources Sample from the black Power BI header bar to see detailed information about the dashboard.
Compare currently active and former employees
Let’s explore data for currently active employees and employees who no longer work for the company.
On the dashboard, select the Active Employee Count by Age Group tile.
The Human Resources Sample report opens to the Active Employees vs. Separations page.
Look at these items of interest:
The two combo charts on the left show the year-over-year change for active employees and employee separations. We have more active employees this year due to rapid hiring, but also more separations than last year.
In August, we had more separations compared to other months. Select the different age groups, genders, or regions to see if you can find any outliers.
Looking at the pie charts, we notice we have an even split in our active employees by gender and age groups. Select different age groups to see how the gender split differs by age. Do we have an even split by gender in every age group?
Reasons for separation
Let’s look at the report in Editing View. You can change the pie charts to show employee separations data instead of active employee data.
Select Edit report in the upper-left corner.
Select the Active Employee Count by Age Group pie chart.
In Fields, select Employees to expand the Employees table. Clear Active Employee Count to remove that field.
Select Separation Count in the Employees table to add it to the Values box in the Fields area.
On the report canvas, select the Voluntary bar in the Separation Count by Separation Reason bar chart.This bar highlights those employees who left voluntarily in the other visuals in the report.
Select the 50+ slice of the Separation Count by Age Group pie chart.
Look at the line chart in the lower-right corner. This chart is filtered to show voluntary separations.
Notice the trend in the 50+ age group. During the latter part of the year, more employees over age 50 left voluntarily. This trend is an area to investigate further with more data.
You can also follow the same steps for the Active Employee Count by Gender pie chart, changing it to separations instead of active employees. Look at the voluntary separation data by gender to see if you find any other insights.
Select Human Resource Sample from the top nav pane to return to the dashboard. You can choose to save the changes you’ve made to the report.
Bad hires
The last area to explore is bad hires. Bad hires are defined as employees who didn’t last for more than 60 days. We’re hiring rapidly, but are we hiring good candidates?
Select the Bad Hires as % of Actives by Age Group dashboard tile. The report opens to tab three, Bad Hires.
Select Northwest in the Region slicer on the left and select Male in the Bad Hire Count by Gender donut chart. Look at the other charts on the Bad Hires page. Notice there are more male bad hires than females and many Group A bad hires.
If you look at the Bad Hire Count by Gender donut chart and select different regions in the Region slicer, you’ll notice that the East region is the only region with more female than male bad hires.
Select the name of the dashboard from the top nav pane to return to the dashboard.
Ask a question in the dashboard Q&A box
In the Q&A question box in the dashboard, you can ask a question about your data by using natural language. Q&A recognizes the words you type and figures out where in your dataset to find the answer.
Select the Q&A question box. Notice that even before you start typing, Q&A displays suggestions to help you form your question.
You can pick one of those suggestions, or enter: show age group, gender, and bad hires SPLY where region is East.
Notice most of the female bad hires are under 30.
Next steps: Connect to your data
This environment is a safe one to play in, because you can choose not to save your changes. But if you do save them, you can always select Get data for a new copy of this sample.
We hope this tour has shown how Power BI dashboards, Q&A, and reports can provide insights into sample data. Now it’s your turn; connect to your own data. With Power BI, you can connect to a wide variety of data sources.
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The last update of 2020 is here! We know you are excited for this update, like a kid excited to open their presents. So this update is our holiday present to you!
What about data protection sensitivity labels making their appearance in Power BI Desktop? Or a new Home List experience in the Service? Want to set a custom to publish message? You got it. Dark mode support for our Android app? Done.
To top it off, there are a couple of new visuals and template apps this month and updates in the data preparation, data connectivity, developers, and embedded space. We even have a couple of pointers to what is coming soon.
Enough to keep you busy during the holidays. Speaking of which, due to the holidays, there will be no release in January. We wish you all safe and happy holidays as we close off 2020. Thank you for being part of our community this year, and looking forward to seeing you in 2021!
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Microsoft announce a new way to visualize your model-driven Power Apps and Dynamics 365 data stored within Dataverse. With a single click, Power BI automatically generates a set of visuals for you to explore and find insights within your data. This integration is a great way to take advantage of the full power of the Power Platform. It’s also the latest extension of the quick creation experience that we’ve already shipped within the Power BI service and in SharePoint and Microsoft lists.
To get started, in your model-driven Power App or Dynamics 365 app, select the Visualize this view button in the app bar of any grid view.
A dialog opens with an automatically generated report with a few fields selected for you in the Your data pane on the right. The visuals within the report will use some or all of your selected fields and potentially other fields from the table that work well with chosen fields.
Just like in the other quick creation experiences, changing the data you see in the report is easy. Just select or unselect fields in the Your data pane to adjust the fields that are influencing the generated visuals. Power BI automatically adds or removes charts to show new visuals.
Also just like in the other experiences, if you want to personalize a specific visual further to get a specific layout or insight, you can use the Personalize this visual option found on the top right when hovering over a visual.
If you want to see all the rows of data Power BI is visualizing, select the Show data table button on the top left, which will add a table showing all the data to the bottom of the report. You can hide the table again by selecting the Hide data table button.
The data being visualized within this generated report is always based on the data currently in the view’s grid. This means if you’ve applied any filters to the grid, that filtered data will be used in the Power BI visuals. For example, if the view is filtered down to just 15 rows of data, only 15 rows will be visualized through Power BI.
This makes it very easy to iteratively explore your data, jumping back and forth between filtering in the grid and visualizing with Power BI, until you find the insights you’re looking for.
We’re currently previewing this feature within Power Apps, so for the option to show, an admin will need to enable it through the Power Apps Maker portal. You can read this article to learn more about configuring app properties within the Power Apps Maker portal.
Currently, the report that’s generated within the app is temporary and can only be used for personal exploration. This means that it can’t currently be shared or saved. It will also time out after a set amount of time, currently one hour. In future updates, we plan to both improve the timeout duration and also add new functionality to support saving it into a Power BI workspace.
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Business intelligence (BI) reporting tools help an organization gather, consolidate, and derive value from its raw data. These tools allow users to analyze their data in-depth, improving decision-making at every level in the organization. Various BI reporting tools are about 80-85% similar in terms of functionalities and features. Different BI tools cater to different user needs like Self Service Reporting, Advanced Analytics, Enterprise-level reporting, etc.
There are certain expectations from a BI reporting tool when it comes to evaluating them based on the below-mentioned parameters:
1. Self Service: Self-service business intelligence (SSBI) is an approach to data analytics that enables business users to access and work with corporate data even though they do not have a background in statistical analysis, BI, or data mining.
An ideal self-service BI reporting tool should qualify on the below-mentioned parameters:
• Visualization & Intuitiveness: Ability to present KPI Driven Visual aids for quickly getting a business pulse at that time.
• Data Blending: Ability to join/blend data from multiple sources like excel and data marts.
• Report Templates: Ability to create report templates and reuse them
• Web-Based Modifications: Ability for end consumers/users to change the format of the report, slice and dice, and save it.
• Export Functionality: Ability to export data to PDF, Excel, and other commonly used platforms.
• Report Sharing: Ability to deliver a report to a mailbox or any specific location.
• Self-Scheduling and Refresh: Ability for user to self-subscribe to schedules or refresh reports on-demand/event-based.
2. Advanced Analytics: Advanced analytics goes beyond mathematical calculations such as sums and averages. It generates new information, identifies patterns and dependencies, and calculates forecasts.
An ideal advanced analytics BI reporting tool should qualify on the below-mentioned parameters:
• Data Capturing: Ability to enable processing and analysis of large amounts of data.
• Data Mining: Data and text mining may be used to find specific trends or pieces of data.
• Predictive Analysis: Ability to use techniques associated with data mining, machine learning, statistical analysis, and others to generate highly accurate predictions about future business trends
• Statistics: Ability to figure out what future trends or results might come about based on the statistics being reviewed
3. Enterprise level reporting: Enterprise reporting is the creation and distribution of reports concerning business performance to key decision-makers in an organization. This may include reports on metrics on key performance indicators or information curated for day-to-day activities. Various factors such as operational reporting, database connectivity support, and user authentication are essential from an enterprise standpoint.
An ideal enterprise-level BI reporting tool should qualify on the below-mentioned parameters:
• Data authorization: Data authorization with inheritance from business application
• Vendor support for tool: There should be easy-to-access vendor support for the tool.
• Pixel-perfect reporting: Ability to make reports which can be formatted in their components down to the individual pixel level
Let us consider 3 leading BI reporting tools and evaluate them based on different parameters.
MicroStrategy: MicroStrategy is an enterprise analytics platform that delivers Dashboards, Visualizations, Mobile apps and supports custom solutions.
Salient features:
• Reusability: Metadata created in MicroStrategy can be reused in the same project many times
• Supports Self Service BI: Supports Self Service BI along with other powerful tools to create reports/dashboards
• Supports a full range of BI applications: Supports a full range of BI applications from departmental BI (small workgroups) to Enterprise BI
• Massive Data access: Can access massive amounts of data from different data sources like EDW and Transactional
Tableau: Tableau helps in simplifying raw data in a very easily understandable format. Data analysis is very fast with Tableau, and the visualizations created are in the form of dashboards and worksheets.
Salient features:
• Supports Self Service BI: Designed from the ground up to support self-service
• Visual Analytics Capabilities: Provides robust visual analytics capabilities to enable data discovery with rapidly promoted roll up and drill-down capabilities
• Data Blending: Easy to use report data blending options facilitate merging multiple data sources
• Server Component Features: The server components provide scalability, access authorization, scheduling, and governance
• Distribution: Distribution is via a variety of client interfaces like Web Browser and Mobile
Power BI: Power BI enables users to gather business insights from both on-premise and cloud-stored data in a dynamic, interactive visualization at the low cost of ownership.
Salient features:
• Content Packs: Power BI uses Content Packs, which has dashboard reports, data models, and embedded queries.
• Custom Visualization: Power BI has a library of custom visualization. If the business needs are different, then so should the visuals.
• Access to a variety of Data sources: Power BI Desktop includes a huge array of on-premise and cloud data sources.
• Print Dashboard: Power BI provides a unique feature for printing dashboards, which can be handy in board meetings and discussions.
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The Customer Profitability sample contains a dashboard, report, and dataset for a company that manufactures marketing materials. This dashboard was created by a CFO to see key metrics about their five business unit managers (executives), products, customers, and gross margins (GM). At a glance, they can see what factors are impacting profitability.
This sample shows how you can use Power BI with business-oriented data, reports, and dashboards. It was created by obviEnce with real data, which has been anonymized. The data is available in several formats: a built-in sample in the service, a .pbix Power BI Desktop file, or an Excel workbook. See Samples for Power BI.
This tutorial explores the built-in Customer Profitability sample in the Power BI service. Because the report experience is similar in Power BI Desktop and in the service, you can also follow along by using the sample .pbix file in Power BI Desktop.
You don’t need a Power BI license to explore the samples in Power BI Desktop. If you don’t have a Power BI Pro or Premium Per User (PPU) license, you can save the sample to your My Workspace in the Power BI service.
Open the Power BI service (app.powerbi.com), sign in, and open the workspace where you want to save the sample.
If you don’t have a Power BI Pro or Premium Per User (PPU) license, you can save the sample to your My Workspace.
In the bottom-left corner, select Get data.
On the Get Data page that appears, select Samples.
Select Customer Profitability Sample, then choose Connect.
Power BI imports the sample, adding a new dashboard, report, and dataset to your current workspace.
Get the .pbix file for this sample
Alternatively, you can download the Customer Profitability sample as a .pbix file, which is designed for use with Power BI Desktop.
Get the Excel workbook for this sample
If you want to view the data source for this sample, it’s also available as an Excel workbook. The workbook contains Power View sheets that you can view and modify. To see the raw data, enable the Data Analysis add-ins, and then select Power Pivot > Manage. To enable the Power View and Power Pivot add-ins, see Explore the Excel samples in Excel for details.
What is our dashboard telling us?
In the workspace where you saved the sample, find the Customer Profitability dashboard and select it:
Company-wide dashboard tiles
Open the dashboard in the Power BI service. The dashboard tiles give our CFO a view of the high-level company metrics important to them. When they see something interesting, they can select a tile to dig into the data.
Review the tiles on the left side of the dashboard.
Note the following details:
The company’s gross margin is 42.5%.
It has 80 customers.
It sells five different products.
It had its lowest revenue % variance to budget in February, followed by the highest in March.
Most of our revenue comes from the east and north regions. Gross margin has never exceeded budget, with the ER-0 and MA-0 business units requiring further investigation.
Total revenue for the year is close to budget.
Manager-specific dashboard tiles
The tiles on the right side of the dashboard provide a team scorecard. The CFO needs to keep track of their managers and these tiles give them a high-level overview of profit, by using GM%. If the GM% trend is unexpected for any manager, then they can investigate further.
By analyzing the manager-specific dashboard tiles, we can make the following observations:
All executives, except Carlos, have already exceeded their target sales. However, Carlos’ actual sales are the highest.
Annelie’s GM% is the lowest, but we see a steady increase since March.
Valery, on the other hand, has seen their GM% drop significantly.
Andrew had a volatile year.
Explore the dashboard’s underlying data
This dashboard has tiles that link to a report and to an Excel workbook.
Open the Excel Online data source
Two tiles on this dashboard, Target vs Actual and Year Over Year Revenue Growth were pinned from an Excel workbook. When you select either of these tiles, Power BI opens the data source: in this case, Excel Online.
Select Target vs Actual. Excel Online opens within the Power BI service.
Notice that the workbook has three tabs worth of data. Open COGS.
Total revenue is exceeding costs by a healthy margin. The shape of the Total revenue line and height of the costs columns are similar. Interact with the data by filtering slicing, drilling, and more. For example, let’s look at Revenue vs COGS for just one Industry.
a. From the Industry slicer, select Retail.
b. We see that only two district managers cover the retail industry: Andrew and Carlos.
c. Total revenue is exceeding costs by a healthy margin until 2014 quarter 3. And looking at the stacked column, we see some strange data that bears further examination. Did we truly have no costs for July? Did we get a refund from a third party?
Continue exploring. If you find something interesting, select Pin from the upper-right corner to pin it to a dashboard.
Use your browser’s back arrow to return to the dashboard.
Open the underlying Power BI report
Many of the tiles on the Customer Profitability sample dashboard were pinned from the underlying Customer Profitability sample report.
Select one of these tiles to open the report in Reading view.
If the tile was created in Q&A, selecting it opens the Q&A window. Select Exit Q&A to return to the dashboard and try a different tile.
The report has three pages. You can select the page you want from the Pages pane on the left.
Team Scorecard focuses on the performance of the five managers and their books of business.
Industry Margin Analysis provides a way to analyze the profitability compared to what’s happening in the entire industry.
Executive Scorecard provides a view of each of the managers, in a custom page size format.
Team Scorecard page
Let’s look at two of the team members in detail and see what insights can be gained:
In the Executive slicer on the left, select Andrew’s name to filter the report page to display only data about Andrew:
For a quick KPI, look at Andrew’s Revenue Status (Total Year); it’s green, which means he’s performing well.
The Revenue % Variance to Budget by Month and Executive chart shows that, except for a dip in February, Andrew is doing well. Andrew’s most dominant region is the east region, which includes 49 customers, and five out of seven products. Andrew’s GM% is not the highest or the lowest.
The RevenueTY and Revenue % Var to Budget by Month chart shows a steady, even-profit story. However, if you filter by selecting the square for Central in the region treemap, you discover that Andrew has revenue only in March and only in Indiana. Is this trend intentional or is it something that needs looking into?
Now on to Valery. In the Executive slicer, select Valery’s name to filter the report page to display data only about Valery.
Notice the red KPI for Revenue Status (Total Year). This item definitely needs further investigation.
Valery’s revenue variance also paints a worrying picture; Valery is not meeting set revenue margins.
Valery has only nine customers, handles only two products, and works almost exclusively with customers in the north region. This specialization could explain the wide fluctuations in the metrics.
If you select the North square in the tree map, it shows that Valery’s gross margin in the north region is consistent with the overall margin.
Selecting each of the other Total Revenue by Region squares tells an interesting story: their GM% ranges from 23% to 79%. Valery’s revenue numbers, in all regions except the north region, are extremely seasonal.
Continue exploring to find out why Valery’s area is not performing well. Look at regions, the other business units, and the next page in the report: Industry Margin Analysis.
Industry Margin Analysis
This report page provides a different slice of the data. It looks at gross margin for the entire industry, broken down by segment. The CFO uses this page to compare company and business unit metrics to industry metrics to help them explain trends and profitability. You might wonder why the Gross Margin % by Month and Executive chart is on this page, because it’s team-specific. Having it here lets us filter the page by business unit manager.
How does profitability vary by industry? How do the products and customers break down by industry? To answer these questions, select one or more industries from the top left (start with the CPG industry). To clear the filter, select the eraser icon.
On the Revenue Var % to Budget, GM%, and RevenueTY by Industry bubble chart, the CFO looks for the largest bubbles, because they have the biggest impact on revenue. To easily see each manager’s impact by industry segment, filter the page by select each manager’s name in turn in the area chart.
As you select each manager in the chart, note the following details:
Andrew’s area of influence spans many different industry segments with widely varying GM% (most on the positive side) and Var%.
Annelie’s chart is similar, except that Annelie only concentrates on a handful of industry segments with a focus on the Federal segment and a focus on the Gladius product.
Carlos has a clear focus on the services segment, with good profit. Carlos has also greatly improved Var% for the High Tech segment and a new segment, Industrial, performed exceptionally well compared to budget.
Tina works with a handful of segments and has the highest GM%, but the mostly small size of the bubbles shows that Tina’s impact on the company’s bottom line is minimal.
Valery, who is responsible for only one product, works in only five industry segments. Valery’s industry influence is seasonal but always produces a large bubble, indicating a significant impact on the company’s bottom line. Do the industry segments explain their negative performance?
Executive Scorecard
This page has a custom page size format.
Dig into the data by asking questions with Q&A
For our analysis, it might be helpful to determine which industry generates the most revenue for Valery. Let’s use Q&A.
From the top of the dashboard, select Ask a question about your data to open the Q&A question box.
Type total revenue by industry for Valery in the question box. Notice how the visualization updates as you type the question.
As you can see, the Services industry is the biggest revenue area for Valery.
Dig deeper by adding filters
Let’s take a look at the Distribution industry.
Open the Industry Margin Analysis report page.
Without selecting any visualizations on the report page, expand the filter pane on the right (if it isn’t already expanded). The Filters pane should display only page level filters.
Locate the filter for Industry and select the arrow to expand the list. Let’s add a page filter for the Distribution industry. First, clear all selections by clearing the Select All checkbox. Then select Distribution only.
The Gross Margin % by Month and Executive chart tells us that only Valery and Tina have customers in this industry and Valery worked with this industry only from June to November.
Select Tina and then Valery in the Gross Margin by Month and Executive chart legend. Notice Tina’s portion of the Total Revenue by Product chart is small compared to Valery.
To see actual revenue, select the Q&A box in the dashboard and enter total revenue by executive for distribution by scenario.
We can similarly explore other industries and even add customers to our visuals to understand causes for Valery’s performance.
Next steps: Connect to your data
This environment is a safe one to play in, because you can choose not to save your changes. But if you do save them, you can always select Get data for a new copy of this sample.
We hope this tour has shown how Power BI dashboards, Q&A, and reports can provide insights into sample data. Now it’s your turn; connect to your own data. With Power BI, you can connect to a wide variety of data sources.
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More and more things are being automated for faster delivery, which is also valid with Power BI. In this article, we look at how to automate the creation of a new Power BI report based on the dataset.
Solution
When working with Power BI daily, sometimes report developers to miss the opportunity to utilize a newly available function that can help out when a “quick” report needs to be developed. In the past, you would have to install and fire up Power BI Desktop and go through a significant design process. The process would include establishing data sources and transformation models and determining the best visuals placed on the design grid. Once the design was finished, that Power BI file would need to be published to the Power BI Service on the web. Such a process would be a fair number of steps to achieve a quick report. However, with a recent upgrade to Power BI, this whole process can be curtailed to a simplified process to establish a quick dashboard with visuals related to a dataset.
Usually, in this section of the tip, a description of installing Power BI Desktop would be provided, but installs are not needed for this particular tip. However, it would be recommended that installing Power BI Desktop would be advantageous for any dashboard developer. You can download the latest version of Power BI desktop to follow along with the examples.
We will actually utilize the Power BI Service to complete the tasks described in this tip for this tip. Thus, you will need access to the Power BI Service through either a work or school account.
From the main Power BI home page, two options are available for creating a new report online, via the Power BI Service. Either the “+” plus sign Create button on the left menu can be selected or the “+ New report” button can be selected in the upper right menu.
Both get you to the same place, which is the Add data to get started (Preview) screen shown below.
Currently only a few options are available to get your data into the report:
You can copy and paste your data set into the entry screen
You can manually enter the data into the entry screen
You can select a currently published dataset
However, only the manual entry or cut and paste method allow for the dashboard report’s auto-generation. Using the “select currently published dataset” will generate a blank report.
Thus, using the entered data manually option opens a data entry grid that allows copying and pasting or simply manually entering the data. Notice the three options available on the design grid. The top dropdown box allows for defining the first row as the header for the table.
For the rows and columns, click on the + buttons as either rows or columns, respectively. Furthermore, the column name can be changed by double-clicking on the column name.
Likewise, the column data type can be adjusted by clicking on the ABC123 button on the left side of each column header. This change can be very helpful as it keeps the data consistent while also preventing certain typing and conversion of data types errors.
In any case, navigating the grid is similar to Microsoft Excel. For example, using the enter key moves the current cell down one cell. Similarly, the data entry can move side to side using the arrow keys to move left and right.
One final note about the design grid, be sure to name your table something appropriate and contextually sound and logical; this is the name of the dataset that users see.
Be sure not to have a cell selected; if you do, the copy/paste will put all the data in a single cell.
A second issue that you can run into pertains to the data types. Power BI allows the dashboard designer to change the data type to something that does not match the actual data in the column(s).
As shown below, the product field allowed the selection of a whole number for the Product column, which contains alpha characters.
Only upon clicking the Auto-create report button does an error appear. One impressive feature of the error message is that it provides row numbers where the errors could be occurring. That can be helpful if the number of problem rows is minimal (one or two for instance) in an extensive data set.
Three options are available once the data set has been copied in or manually entered to create the report. We are focusing on the Auto-create option. The create a blank report option is similar to the design experience in Power BI desktop, while the generate a data set only option will add the dataset to available datasets on the service.
Clicking on the Auto-create report creates and opens the newly designed with a set of suggested visuals. In the screen print below, you can see that Power BI created 8 visuals, six-column charts, and 2 cards in the upper right corner. Notice in the bottom right corner that the Preview status is highlighted. Power BI makes certain assumptions about the data to provide the initial list of charts.
The robust feature here is that the newly designed report allows for other charts and will automatically make the changes. For instance, if Discount Band is selected from the field list, a new set of charts is added on the right side with the sum of units sold and sum of COGS all by Discount Band. In this case, Power BI knows that Discount Band would be a category field.
Similarly, unchecking a field will remove the related charts to that field. In the illustration below, the country was removed.
In the above, examples, categories were added or removed. New measures can also be selected which would add a whole new row of charts. Thus, using the below example, the Gross Sales measure is selected, and a new set of 3 charts based on Gross Sales is added, plus a new card at the top of the dashboard is added.
However, if you attempt to add a 4th measure, the error shown in the following screen print results. Power BI currently only allows 3 measures (rows) and 4 categories (columns). Trying to add fields beyond those numbers will result in an error.
Additionally, you will notice on these screens you have limited editing capabilities including not being able to make formatting change or changes to the field lists on a particular visual. Filters and sorting can be applied to the visuals, though.
When you are satisfied with the report, clicking on the save button save the report and the report will automatically be saved to your workspace area on the Power BI Service.
Even with the report saved, the interchanging of categories and measures still can be made by dashboard designers AND dashboard viewers and these changes can be saved by report designers. This dashboard is considered to be using the summarize pane.
Also, at this point, the report can be edited similar to any other report. However, you will receive the below warning. The warning is basically telling you that once you switch to edit mode, the Auto-created Summarize pane options will no longer be in effect and each visual must be modified on its own (like you would do in other reports).
In this tip, we reviewed the process of allowing Power BI to Auto-Create a report for you based on data input or copy into a new dataset. Currently, this method is the only supported option for entering data, but other options are expected in the future for this preview feature.
When people are asked to define a “financial report”, many would answer that a financial report is ‘a table with numbers’. Financial reports are often associated with Microsoft Excel since we live in a world where you can export almost anything into MS Excel and knowledge of MS Office is considered a de facto basic skill for any employee. For this reason, the words ‘financial report’ has become a synonym of an Excel sheet. However, employees who have already faced implementing a new data strategy in their organization or introducing new business intelligence concepts in their work would say that a report is a visual representation of information with charts and graphs, rather than just a table with figures.
Then, what is Dashboard? An Oxford dictionary says it is ‘the panel facing the driver of a vehicle or the pilot of an aircraft, containing instruments and controls’ (Oxford University Press, n.d.).’ At first sight, it sounds confusing in our context, doesn’t it? Nevertheless, imagine that you are driving a car and sitting in front of the driver’s dashboard. But your car is more than an ordinary vehicle – it is the entire organization you are working. What would you place on this dashboard? What measures the health and growth of your company and is vital for a safe ‘road trip’? What KPIs are important for your team leader or head of the department?
In the diverse variety of business intelligence tools available on the software market, a report can be defined differently. However, Dashboard has always been serving one main purpose: to represent KPIs via gauges, tiles with big numbers, intuitively understandable trends, etc. In this article, we will look at similar features of reports and dashboards in Power BI and discuss their distinctions.
Report in Power BI
Each Power BI Desktop file (file with ‘pbix’ extension) represents one report. At the same time, you may see that in Power BI Desktop you can have multiple tabs or, according to the Microsoft terminology, pages. On top of that, each of the pages may contain several visuals (see common visual examples here: Visualization types in Power BI).
Let’s consider, for instance, a sample Microsoft Power BI file which you can download from Microsoft GitHub account by using this link or from the attachment to this article:
On the picture above, we can see that ‘1’ and ‘2’ are visuals located on the ‘Overview’ page. At the same time, ‘Overview’, ‘Germany’, ‘Canada’ and other tabs on the bottom – ‘3’ – represent Power BI pages. All the pages are parts of one report associated with the file – 2018SU05 Blog Demo – May.pbix:
Overall, the relationship between visuals, pages, report and ‘pbix’ file looks like this:
Visual types, pages, report and file names are given as examples. In reality, you are not required to create an Overview page as the first one and detailed pages as the second one; although, it is considered to be a good approach to tell your data story starting from general information and then going deeper into details. Also, you can choose any number of visuals having diverse types for any page of your report.
Dashboard in Power BI
A dashboard can be combined with one or several Power BI reports. However, this doesn’t mean that a dashboard should contain all the visuals from all the pages of a report. Instead, you define one-by-one each visual of the report to be included into Power BI Dashboard. I’d like to emphasize that – usually, you are not choosing the whole page of a report to be included, but a particular visual from a particular page. However, the ability to pin the entire report page to a dashboard also exists.
Furthermore, it is worth mentioning that if you are using Power BI Report Server – an on-premises version of Power BI – you cannot create Power BI dashboards. Similarly, you cannot create a dashboard in Power BI Desktop: Power BI service (app.powerbi.com) is the only place where the dashboard can live (at least, it is so at the moment of writing this article).
To create a simple dashboard, you need to publish your Power BI report to Power BI service. Let’s do this with the sample file that we used in the previous section. Sign in to your Power BI account and click on ‘publish:’
You can choose any workspace you have, for example, your personal workspace ‘My workspace’:
Once the report is published, navigate to the ‘reports’ tab in your workspace in Power BI online service:
Then, click on ‘edit report:’
Now, you can add your visual to a dashboard. Click on any visual and then, on the top of the visual, click on ‘Pin visual’:
You will need to provide a name for a dashboard:
Do this for several visuals from different pages. Choose any visuals you like. Finally, click on ‘My Workspace’ on the top and then on your newly created dashboard:
By dragging and dropping, you may rearrange your dashboard tiles:
If you click on any tile on the dashboard, you will be redirected to the report page containing this visual.
Please note that you may add visuals from different reports into one dashboard:
(Microsoft, n.d.)
The example above, basically, shows how dashboards work: you may consume the critical information, but you are not supposed to interact with visuals on the dashboard. A dashboard may be thought about as a website’s homepage – in this case, your analytical website. This page serves as a summary of your analytical content and an entryway to your reports. Overall, having a dashboard is important for a natural navigation flow that should start from summarized information and go into detail where required.
Dashboards vs. Reports
For a beginner, Power BI reports and dashboards often seem to be something very similar. Indeed, the difference may be only felt after you have created a couple of reports with several visuals and have been utilizing them for several weeks. Nevertheless, let’s consider the key differences below.
Firstly, you can create the dashboard only in Power BI service rather than in Power BI Desktop, whereas reports can be created and utilized in both Power BI Desktop and Power BI Service. Additionally, you cannot create a dashboard in Power BI Report Server. Secondly, a dashboard always has one page with content that cannot be filtered or sliced, while a report can have one or many fully interactive pages. Finally, in general, there is plenty of customizations available in a report view and not available for dashboard customization.
You need a report: when you need to actively consume information via interaction, slicing and dicing, drilling down and up while looking for trends, dependencies, and their underlying causes. You are supposed to use reports to explore your data.
You need a dashboard: when you have many reports with many pages, you need an entry point for data consumption and a summary of contents on one canvas.
What Happens In Practice
In practice, BI teams do not always use both dashboards and reports, even in Power BI Service (Power BI online). For example, you cannot create content in Power BI software without designing a report, but you can create and consume visuals without dashboard(s). Also, many Power BI users say that they are using Power BI dashboards while they are interacting only with Power BI reports: for a Power BI rookie, any individual page of a report looks identical to a dashboard.
To sum up, if you have several reports with many pages, it makes sense to render the most critical information on a dashboard: the dashboard will serve as a landing page for your analytical portal: by clicking on any tile on the dashboard a user is being navigated to the page of the report containing the visual from the tile clicked. However, you can always achieve similar functionality by creating a summary report page with buttons and bookmarks, but the process would become more complicated. The essence is that dashboards are created for static observations, whereas reports are designed for a highly interactive experience. Usually, you naturally start building dashboards when you realize that you have too many reports confusing you and your management.
https://nexumbs.com/wp-content/uploads/2021/11/Dashboards-vs-Report.jpg7201280Nexumhttps://nexumbs.com/wp-content/uploads/2021/03/logo.pngNexum2021-11-02 19:14:172021-11-04 19:29:48Power BI Reports vs Dashboards
The new platform assures reliable, unmatched support for large-scale analytics, simple low-overhead administration, and introduces “Autoscale” — an optional add-on providing automatic temporary upscaling to address the ever-dynamic demand for computing power. Now more than ever before, Power BI Premium capacities enable unmatched analytics solutions delivery on an enterprise-scale, both efficient and cost-effective. The new platform serves as the bedrock on top of which new and exciting Power BI capabilities will be built from hereon, and using this platform will be the key to unlocking the full potential in all upcoming new features.
Administrators of next-gen premium capacities will find it easier than ever to track the essential resources a Premium capacity uses, know when opting-in to overload slowdown protection via Autoscale is advisable, or if getting a larger capacity is recommended.
After a year in preview, the next-gen platform is now battle-proven to meet the demands of the broadest range of analytics solutions: self-service business, datasets, centrally curated and distributed pixel-perfect reports, and anything in between.
Your capacity’s cpu power is derived from how many backend cores it has, with each backend core adding 30 seconds of CPU processing power to your total power.
During the preview period, Autoscale was enabled free of charge to allow early adopters to grow accustomed to the new platform and adapt any operational practices to its capabilities. Now that the platform is Generally Available, Power BI will begin charging for Autoscale cores that are added to each capacity per the previously announced for Autoscale. Autoscale charges will begin taking place on November 4th 2021.
Power BI Premium Generation 2, referred to as Premium Gen2 for convenience, is an improved and architecturally redesigned generation of Power BI Premium.
Premium Gen2 provides the following updates or improved experiences:
Ability to license Premium Per User in addition to by capacity.
Enhanced performance on any capacity size, anytime: Analytics operations run-up to 16X faster on Premium Gen2. Operations will always perform at top speed and won’t slow down when the load on the capacity approaches the capacity limits.
Greater scale:
– No limits on refresh concurrency, no longer requiring you to track schedules for datasets being refreshed on your capacity
– Fewer memory restrictions
– Complete separation between report interaction and scheduled refreshes
Improved and streamlined metrics with clear and normalized capacity utilization data depends only on the complexity of analytics operations the capacity performs, not on its size, the level of load on the system while performing analytics, or other factors. With the improved metrics, utilization analysis, budget planning, chargebacks, and the need to upgrade are visible with built-in reporting.
Autoscale is an optional feature that automatically adds one v-core at a time for 24-hour periods when the load on the capacity exceeds its limits, preventing slowdowns caused by overload. Additional v-cores are charged to your Azure subscription on a pay-as-you-go basis. See using Autoscale with Power BI Premium for steps on how to configure and use Autoscale.
Reduced management overhead with proactive and configurable admin notifications about capacity utilization level and load increasing.
Enabling Premium Gen2
Enable Premium Gen2 to take advantage of its updates. To enable Premium Gen2, take the following steps:
In the admin portal, navigate to Capacity settings.
Select Power BI Premium.
If you have already allocated capacity, select it.
A section appears titled Premium Generation 2, and in that section is a slider to enable Premium Generation 2.
Move the slider to Enabled.
The following short video shows how to enable Premium Gen2.
Workspaces reside within capacities. Each Power BI user has a personal workspace known as My Workspace. Additional workspaces known as workspaces can be created to enable collaboration. By default, workspaces, including personal workspaces, are made in the shared capacity. When you have Premium capacities, both My Workspaces and workspaces can be assigned to Premium capacities.
Capacity administrators automatically have their my workspaces assigned to Premium capacities.
Capacity nodes for Premium Gen2
With Premium Gen2 and Embedded Gen 2, the amount of memory available on each node size is set to the limit of the memory footprint of a single artifact and not to the cumulative consumption of memory. Thus, for example, in Premium Gen2 P1 capacity, only a single dataset size is limited to 25 GB, compared to the original Premium, where the total memory footprint of the datasets being handled simultaneously was limited to 25 GB.
Refresh in Premium Gen2
Premium Gen2 and Embedded Gen 2 don’t require cumulative memory limits, and therefore concurrent dataset refreshes don’t contribute to resource constraints. There is no limit on the number of refreshes running per v-core. However, the refresh of individual datasets continues to be governed by existing capacity memory and CPU limits. You can schedule and run as many refreshes as required at any given time, and the Power BI service will run those refreshes at the time planned as a best effort.
Monitoring in Gen2
Monitoring in Premium Gen2 intends to simplify monitoring and management of Premium capacities. Premium Gen2 customers can adapt their monitoring approach from a tool to ensure their Premium capacities are running correctly, into a tool that alerts them if attention should be applied to correct over usage or if more resources are required. In other words, rather than constantly having to monitor for issues and adjust, Premium Gen2 aims to assure that everything is running correctly and only alerts users if they must act.
Updates for Premium Gen2 and Embedded Gen2 — Premium Gen2 and Embedded Gen 2 only require monitoring a single aspect: how much CPU time your capacity needs to serve the load at any moment.
This reduction in the need for monitoring is a departure from the many metrics that the original version of Power BI Premium required. As a result, organizations that created a cadence of monitoring and reporting on their original Premium capacities will need to transition their existing rhythm of monitoring their Premium Gen2 capabilities due to the streamlined metrics and monitoring requirements of Premium Gen2.
In Premium Gen2, if you exceed your CPU time per the SKU size you purchased, your capacity either autoscales to accommodate the need (if you’ve optionally enabled autoscale), or throttles your interactive operations, based on your configuration settings.
In Embedded Gen 2, your capacity throttles your interactive operations based on your configuration settings if you exceed your CPU time per the SKU size you purchased. To autoscale in Embedded Gen 2, see Autoscaling in Embedded Gen2.
Updates for Premium Gen2
Premium Gen2 and Embedded Gen 2 capacities use the Capacity Utilization App.
In Premium Gen2 and Embedded Gen2, there is no memory management for Paginated reports. With Premium Gen2 and Embedded Gen2, Paginated reports are also supported on the EM1-EM3 and A1-A3 SKUs.
When using Premium Gen2, Paginated reports in Power BI benefit from the architectural and engineering improvements reflected in Premium Gen2. The following sections describe the benefits of Premium Gen2 for Paginated reports.
Broader SKU availability — Paginated reports running on Premium Gen2 can run reports across all available embedded and Premium SKUs. In addition, billing is calculated per CPU hour, across a 24-hour period. This greatly expands the SKUs that support Paginated reports.
Dynamic scaling — With Premium Gen2, challenges associated with spikes in activity, or need for resources, can be handled dynamically as the need arises.
Improved caching — Before Premium Gen2, Paginated reports were required to perform many operations in the context of memory allocated on the capacity for the workload. Now, using Premium Gen2, reductions in the required memory for many operations enhance customers’ ability to perform long-running operations without impacting other user sessions.
Enhanced security and code isolation — With Premium Gen2, code isolation can occur at a per-user level rather than per-capacity, as was the case in the original Premium offering.
Power BI Premium Gen2 is a tenant-level Microsoft 365 subscription available in two SKU (Stock-Keeping Unit) families:
P SKUs (P1-P5) for embedding and enterprise features require a monthly or yearly commitment, billed monthly, and include a license to install Power BI Report Server on-premises.
EM SKUs (EM1-EM3) for organizational embedding, requiring a yearly commitment, are billed monthly. EM1 and EM2 SKUs are available only through volume licensing plans. You can’t purchase them directly.
In addition, Premium Per User has the benefits available with Premium Gen2, but on an individual user basis.
Purchasing
Administrators purchase power BI Premium subscriptions in the Microsoft 365 admin center. Specifically, only Global administrators or Billing Administrators can purchase SKUs. When purchased, the tenant receives a corresponding number of v-cores to assign to capacities, known as v-core pooling. For example, buying a P3 SKU provides the tenant with 32 v-cores. To learn more, see How to purchase Power BI Premium.
Limitations in Premium Gen2
The following known limitations currently apply to Premium Gen2:
There’s a 225-second limitation for rendering Power BI visuals. Therefore, visuals that take longer to generate will be timed-out and will not display.
Analysis services features in Premium Gen2 are only supported on the latest client libraries. Estimated release dates for dependent tools to support this requirement are:
Memory restrictions are different in Premium Gen2 and Embedded Gen 2. In the first generation of Premium and Embedded, memory was restricted to a limited amount of RAM used by all artifacts simultaneously running. In Gen2, there is no memory limit for the capacity as a whole. Instead, individual artifacts (such as datasets, dataflows, paginated reports) are subject to the following RAM limitations:
– A single artifact cannot exceed the amount of memory the capacity SKU offers.
-The limitation includes all the operations (interactive and background) being processed for the artifact while in use (for example, while a report is being viewed, interacted with, or refreshed).
-Dataset operations like queries are also subject to individual memory limits, just as they are in the first version of Premium.
-To illustrate the restriction, consider a dataset with an in-memory footprint of 1 GB, and a user initiating an on-demand refresh while interacting with a report based on the same dataset. Two separate actions determine the amount of memory attributed to the original dataset, which may be larger than two times the dataset size:
-The dataset needs to be loaded into memory.
-The refresh operation will cause the memory used by the dataset to double, at least, since the original copy of data is still available for active queries while the refresh is processing an additional copy. However, once the refresh transaction commits, the memory footprint will reduce.
-Report interactions will execute DAX queries. Each DAX query consumes a certain amount of temporary memory required to produce the results. Therefore, each query may consume a different amount of memory and be subject to the query memory limitation described.
The following table summarizes all the limitations that are dependent on the capacity size:
Power BI Premium Gen2 architecture
Architectural changes in Premium Gen2, especially around how CPU resources are allocated and used, enables more versatility in offerings, and more flexibility in licensing models. For example, the new architecture enables offering Premium on a per-user basis, offered as Premium Per User. The architecture also provides customers with better performance, and better governance and control over their Power BI expenses.
The most significant update in the architecture of Premium Gen2 is the way capacities’ back-end v-cores (CPUs, often referred to as v-cores) are implemented:
In the original version of Power BI Premium, backend v-cores were reserved physical computing nodes in the cloud, with differences in the number of v-cores and the amount of onboard memory according to the customer’s licensing SKU. Customer administrators were required to keep track of how busy these nodes were, using the Premium metrics app. They had to use the app and other tools to determine how much capacity their users required to meet their computing needs.
Each administrator had the ability to tweak and configure capacities to avoid resource contention between workloads (datasets, dataflows, paginated reports, and AI) or other performance impactful effects to make sure capacity performance remained tuned or acceptable.
In Premium Gen2, backend v-cores are implemented on regional clusters of physical nodes in the cloud, which are shared by all tenants using Premium capacities in that Power BI region. The regional cluster is further divided into specialized groups of nodes, where each group handles a different Power BI workload (datasets, dataflows, or paginated reports). These specialized groups of nodes help avoid resource contention between fundamentally different workloads running on the same node.
The contents of workspaces assigned to a Premium Gen2 capacity is stored on your organizations capacity’s storage layer, which is implemented on top of capacity-specific Azure storage blob containers, similar to the original version of Premium. This approach enables features like BYOK to be used for your data.
When the content needs to be viewed or refreshed, it is read from the storage layer and placed on a Premium Gen2 backend node for computing. Power BI uses a placement mechanism that assures the optimal node is chosen within the proper group of computing nodes. The mechanism typically places new content on the node with the most available memory at the time the content is loaded, so that the view or refresh operation can gain access to the most resources and can perform optimally.
As your capacity renders and refreshes more content, it uses more computation nodes, each with enough resources to complete operations fast and successfully. This means your capacity may use multiple computational nodes and in some cases, content might even move between nodes due to the Power BI service performing internal load-balancing across nodes or resources. When such load balancing occurs, Power BI makes sure content movement doesn’t impact end-user experiences.
There are several positive results from distributing backend processing of content (datasets, dataflows, and paginated reports) across shared backend nodes:
The shared nodes are at least as large as an original Premium P3 node, which means there are more v-cores to perform any operations, which can increase performance by up to 16x when comparing to an original Premium P1.
Whatever node your processing lands on, the placement mechanism makes sure memory remains available for your operation to complete, within the applicable memory constraints of your capacity. (see limitations section of this doc for full detail of memory constraints)
Internal noisy neighbor problems in your capacity don’t occur, since each of the view and refresh operations uses its own set of physical v-cores, with their own memory, on different computing nodes.
Cross-workloads resource contention is prevented by separating the shared nodes into specialized workload groups. As a result of this separation, there are no controls for paginated report workloads.
The limitations on different capacity SKUs are not based on the physical constraints as they were in the original version of Premium; rather, they are based on an expected and clear set of rules that the Power BI Premium service enforces:
Total capacity CPU throughput is at or below the throughput possible with the v-cores your purchased capacity has.
Memory consumption required for viewing and refresh operations remains within the memory limits of your purchased capacity.
6. Because of this new architecture, customer admins do not need to monitor their capacities for signs of approaching the limits of their resources, and instead are provided with clear indication when such limits are met. This significantly reduces the effort and overhead required of capacity administrators to maintain optimal capacity performance.
Premium Gen2 capacity load evaluation
To enforce CPU throughput limitations, Power BI evaluates the throughput from your Premium Gen2 capacity on an ongoing basis.
Power BI evaluates throughput every 30 seconds. It allows operations to complete, collects execution time on the shared pool physical node’s CPUs, and then for all operations on your capacity, aggregates them into 30-second CPU intervals and compares the results to what your purchased capacity is able to support.
The following image illustrates how Premium Gen2 evaluates and completes queries.
Let’s look at an example: a P1 with four backend v-cores can support 120 seconds (4 x 30 seconds = 120) of v-core execution time, also known as CPU time.
The aggregation is complex. It uses specialized algorithms for different workloads, and for different types of operations, as described in the following points:
Slow-running operations, such as dataset and dataflow refresh, are considered background operations since they typically run in the background and users don’t actively monitor them or look at them visually. Background operations are lengthy and require significant CPU power to complete during the long process. Power BI spreads CPU costs of background operations over 24 hours, so that capacities don’t hit maximum resource usage due to too many refreshes running simultaneously. This allows Power BI Premium Gen2 subscribers to run as many background operations as allowed by their purchased capacity SKU, and doesn’t limit them like the original Premium generation.
Fast operations like queries, report loads, and others are considered interactive operations. The CPU time required to complete those operations is aggregated, to minimize the number of 30-seconds windows that are impacted following that operation’s completion.
Premium Gen2 background operation scheduling
Refreshes are run on Premium Gen2 capacities at the time they are scheduled, or close to it, regardless of how many other background operations were scheduled for the same time. Datasets and dataflows being refreshed are placed on a physical processing node that has enough memory available to load them, and then begin the refresh process.
While processing the refresh, datasets may consume more memory to complete the refresh process. The refresh engine makes sure no artifact can exceed the amount of memory that their base SKU allows them to consume (for example, 25 GB on a P1 subscription, 50 GB on a P2 subscription, and so on).
How capacity size limits are enforced when viewing reports
Premium Gen2 evaluates utilization by aggregating utilization records every 30 seconds. Each evaluation consists of 2 different aggregations:
Interactive utilization
Background utilization
Interactive utilization is evaluated by considering all interactive operations that completed on or near the current 30-second evaluation cycle.
Background utilization is evaluated by considering all the background operations that completed during the past 24 hours. Each background operation contributes only 1/2880 of its total CPU cost (2880 is the number of evaluation cycles in a 24-hour period).
Each capacity consists of an equal number of frontend and backend v-cores. The CPU time measured in utilization records reflect the backend v-cores’ utilization, and that utilization drives the need to autoscale. Utilization of frontend v-cores is not tracked, and you cannot convert frontend v-cores to backend v-cores.
If you have a P1 subscription with 4 backend v-cores, each evaluation cycle quota equates to 120 seconds (4 x 30 = 120 seconds) of CPU utilization. If the sum of both interactive and background utilizations exceeds the total backend v-core quote in your capacity, and you have not optionally enabled autoscale, the workload for your Gen2 capacity will exceed your available resources, also called your capacity threshold. The following image illustrates this condition, called overload, when autoscale is not enabled.
In contrast, if autoscale is optionally enabled, if the sum of both interactive and background utilizations exceeds the total backend v-core quota in your capacity, your capacity is automatically autoscales (raised) by one v-core for the next 24 hours.
The following image shows how autoscale works.
Autoscale always considers your current capacity size to evaluate how much you use, so if you already autoscaled into one v-core, that v-core is spread evenly at 50% for frontend utilization and 50% for backend utilization. This means your maximum capacity is now at (120 + 0.5 * 30 = 135 seconds) of CPU time in an evaluation cycle.
Autoscale always ensures that no single interactive operation can account for all of your capacity, and you must have two or more operations occurring in a single evaluation cycle to initiate autoscale.
Using Premium Gen2 without autoscale
If a capacity’s utilization exceeded 100% of its resources, and it cannot initiate autoscale due to autoscale being turned off, or already being at its maximum v-core value, the capacity enters a temporary interactive request delay mode. During the interactive request delay mode, each interactive request (such as a report load, visual interaction, and others) is delayed before it is sent to the engine for execution.
The capacity stays in interactive request delay mode if the previous evaluation is evaluated at greater than 100% resource utilization.
Using Autoscale with Power BI Premium
Power BI Premium offers scale and performance for Power BI content in your organization. With Power BI Premium Gen2, many improvements are introduced including enhanced performance, greater scale, improved metrics. In addition, Premium Gen2 enables customers to automatically add compute capacity to avoid slowdowns under heavy use, using Autoscale.
Autoscale uses an Azure subscription to automatically use more v-cores (virtual CPU cores) when the computing load on your Power BI Premium subscription would otherwise be slowed by its capacity. This article describes the steps necessary to get Autoscale working for your Power BI Premium subscription. Autoscale only works with Power BI Premium Gen2.
To enable Autoscale, the following steps need to be completed:
Select and configure an Azure subscription to use with Autoscale
Configure Power BI Premium to use the selected Azure subscription for Autoscale
The following sections describe the steps in detail.
Note — Autoscale isn’t available for Microsoft 365 Government Community Cloud (GCC), due to the use of the commercial Azure cloud.
Embedded Gen 2 does not provide an out-of-the-box vertical autoscale feature. To learn about alternative autoscale options for Embedded Gen2, see Autoscaling in Embedded Gen2
Configure an Azure subscription to use with Autoscale
To select and configure an Azure subscription to work with Autoscale, you need to have contributor rights for the selected Azure subscription. Any user with Account admin rights for the Azure subscription can add a user as a contributor. In addition, you must be an admin for the Power BI tenant to enable Autoscale.
To select an Azure subscription to work with Autoscale, take the following steps:
Log into the Azure portal and select Subscriptions from the left pane. In the following image, the highlighted subscription is called Pay-As-You-Go.
2. Select a subscription. Once selected, you need to create a Resource group to use with Autoscale. Select Resource group from the Settings selections for your selected subscription. Then select the Add button to create a new Resource group.
3. The Create a resource group window appears, where you can name the resource group. In the following image, the resource group is called powerBIPremiumAutoscaleCores. You can name your resource group whatever you prefer. Just remember the name of the subscription, and the name of your resource group, since you’ll need to select it again when you configure Autoscale in the Power BI Admin Portal.
4. When you’re satisfied with the name of the resource group, select the Review + create button in the bottom left corner of the portal pane. Azure validates the information, after which you select the Create button to create the resource group. Once created, you receive a notification in the upper-right corner of the Azure portal, similar to the following:
Okay, you’ve selected the Subscription in the Azure portal that you’ll use for Autoscale, and created a Resource group for that subscription. The next step is to enable Autoscale in the Power BI Admin portal, and link it to the resource group you just created.
Considerations for preview release
When Autoscale is launched in preview, a window to enable customers to become accustomed to the usage levels and CPU core utilization is being provided. During the initial window, charges to the configured Azure subscription used for Autoscale will not be applied. That window is anticipated to be 30 days. The best way to become accustomed to the level of usage your organization is to sign up for utilization alert notifications in the Power BI Admin portal, and to monitor alerts for utilization levels.
Paginated Reports are not included in the process of determining the level of utilization, and whether to Autoscale, during initial window.
Enable Autoscale in the Power BI Admin portal
Once you’ve selected the Azure subscription to use with Autoscale, and created a resource group as described in the previous section, you’re ready to enable Autoscale and associate it with the resource group you created. The person configuring Autoscale must be at least a contributor for the Azure subscription to successfully complete these steps. You can learn more about assigning a user to a contributor role for an Azure subscription.
The following steps show you how to enable and associated Autoscale with the resource group.
Open the Power BI Admin portal and select Capacity settings from the left pane. Information about your Power BI Premium capacity is displayed.
2. Autoscale only works with Power BI Premium Gen2. Enabling Gen2 is easy: just move the slider to Enabled in the Premium Generation 2 box.
3. Select the Manage auto-scale button to enable and configure Autoscale, and the Auto-scale settings pane appears. Select the Enable auto scale.
4. You can then select the Azure subscription to use with Autoscale. Only subscriptions available to the current user are displayed, which is why you must be at least a contributor for the subscription. Once your subscription is selected, select the Resource group you created in the previous section, from the list of resource groups available to the subscription.
5. Next, assign the maximum number of v-cores to use for Autoscale, and then select Save to save your settings. Power BI applies your changes, then closes the pane and returns the view to Capacity settings, where you can see your settings have been applied. In the following image, there were a maximum of two v-cores configured for Autoscale.
7. Here’s a short video that shows how quickly you can configure Autoscale for Power BI Premium Gen2:
And that’s it — your Power BI Premium Gen2 subscription is now configured to use Autoscale, so users in your organization automatically get the responsiveness they need from their Power BI content and insights, even under periods of heavy use.
Plan your transition to Power BI Premium Gen2
Over the last several months, we’ve been working to make many improvements to Power BI Premium. Changes include updates to licensing, performance, scaling, management overhead, and improved insight to utilization metrics. This next generation of Power BI Premium, referred to as Power BI Premium Gen2, has officially moved from preview to general availability as of October 4, 2021. You can read the announcement about this release in the Power BI blog.
If your organization is using the previous version of Power BI Premium, you’re required to migrate capacities to the modern Gen2 platform. The key dates for you to be aware of are listed below:
October 4, 2021 — Power BI Premium Gen2 is generally available.
November 15, 2021 — We start sending notifications reminding customers to migrate.
January 15, 2022 — Microsoft begins migration of Premium capacities to the modern Gen2 platform for all organizations.
Self-migration to Premium Generation 2
If you want to perform your own migration to the latest platform before January 15, 2022, it’s easy to transition. You simply need to enable Premium Gen2 in the Power BI admin portal. Migrating doesn’t interrupt your Power BI service. The change typically completes within a minute and won’t take more than 10 minutes.
Ready for the next generation? Follow these steps:
From the navigation bar, select Settings > Admin portal > Capacity settings.
3. Select Power BI Premium.
4. If you have already allocated capacity, select it.
5. The section Premium Generation 2 appears.
6. Select the slider to switch the setting to Enabled. This step is demonstrated in the following animation:
Transition from preview to Premium Gen 2 general availability
Customers using Power BI Premium Gen2 in preview don’t need to take any action to transition to the general availability release. However, there are some key dates to consider if you’ve been using Autoscale to balance your capacity needs.
To date, organizations that have enabled Autoscale for capacities have gotten the burst processing benefits of Autoscale for free. Beginning November 4, 2021 we’ll begin charging for Autoscale cores. Take one of the following actions:
You can continue to use Autoscale to enable the automatic use of additional cores during periods of higher-than normal demand on your capacities. Review the pricing details for Premium per capacity add-ons so that you’re aware of upcoming charges.
Or, to avoid Autoscale charges, disable the feature. Autoscale is an optional feature and benefit of the Premium Gen2 platform. You can choose to not use it.
Migration timeline summary
Power BI Premium Gen2 FAQ
What is Power BI Premium Generation 2?
Power BI Premium recently released a new version of Power BI Premium, Premium Gen2. Premium Gen2 will simplify the management of Premium capacities, and reduce management overhead. For more information about Premium Gen2, see Power BI Premium Generation 2.
How can I control the costs of autoscaling?
Autoscaling is an optional feature of Premium Gen2, and is subject to two limits, each if which is configured by Power BI administrators:
Proactive limit — a proactive limit sets the rate of expenses that Autoscale can generate, by limiting the number of autoscale v-cores a capacity can use. For example, by setting a maximum autoscale of v-cores to one v-core, you ensure that the maximum charge you can incur is 30 days of autoscaling with one v-core.
Reactive limit — you can also set a reactive limit to the cost for autoscaling, by setting an expenditure limit on the Azure subscription used with autoscale. If the subscription’s budget is exhausted, Power BI is prevented from using the v-core resources for that subscription, and autoscale shuts off. You can set a budget for the Azure subscription that autoscale uses by following the Azure budget tutorial.
How does resource utilization cause Gen2 to autoscale?
Power BI Premium Gen2 evaluates your level of utilization by aggregating utilization records every 30 seconds. Each evaluation is composed of two different aggregations: Interactive utilization and background utilization.
Interactive utilization is evaluated by considering all the interactive operations that completed on or near the current half-minute evaluation cycle.
Background utilization is evaluated by considering all the background operations that completed during the past twenty-four hours, where each background operation contributes only 1/2880 of its total CPU cost (there are 2880 evaluation cycles in each 24-hour period).
A capacity consists of an equal number of frontend and backend v-cores. The CPU time measured in utilization records reflect the backend v-cores utilization, and this utilization drives the need to autoscale. Utilization of frontend v-cores is not tracked. You cannot convert frontend to backend v-cores.
If you have a P1 subscription with four backend v-cores, each evaluation cycle quota is 4*30 = 120 seconds of CPU utilization. If the sum of both utilizations exceeds the total backend core quota in your capacity, your capacity will autoscale in one v-core for the next 24 hours.
Autoscale always looks at your current capacity size to evaluate how much resource you use. If you have already autoscaled with one v-core, that v-core is spread evenly between frontend and backend at 50% each, meaning your maximum capacity is now at 120+0.5*30 = 135 seconds of CPU time in an evaluation cycle.
Autoscale always makes sure that no single interactive operation can consume all of your capacity, and you must have two or more interactive operations taking place in a single evaluation cycle to initiate autoscale.
What happens to traffic during overload if I don’t autoscale?
If a capacity’s utilization exceeded a 100% and it cannot use autoscale, due to being turned off or already at its maximum v-core utilization value, the capacity enters into a temporary interactive request delay mode, during which each interactive request (such as report load, visual interaction, and so on) is delayed before it is sent to the engine for execution. The amount of delay is proportional to the amount of overload detected. Overload of 100% will incur a delay of 20 seconds, while overloads smaller than 10% are allowed.
The capacity stays in interactive request delay mode if the previous evaluation is at greater than 100% resource usage.
Which operations contribute to interactive utilization, and which to background utilization?
Paginated reports workload — data driven subscriptions renders
AI workloads
How can I use my utilization data to predict my capacity needs?
Your metrics report dataset retains 30 to 45 days of data. You can use the report to indicate how close you are to your capacity’s maximum resources, and if you save monthly snapshots, you can compare them to indicate trends of growth and extrapolate the rate in which you will arrive at 100% utilization of your resources.
How can my utilization data inform me I should turn on autoscale?
Utilization data does not currently indicate whether requests were throttled due to capacity being in interactive request delay mode. The information will be added to the utilization app so admins can determine whether users experienced delays, and to what extent the delays are due to overload without autoscaling.
How can I get notified that I’m approaching my max capacity?
The Capacity management page in the Power BI admin portal has a utilization notification checkbox. Users can choose the threshold at which an alert will be triggered (default is 80%) and the email address to which utilization alerts should be sent.
How much data is Power BI storing? How can I retain more?
The Power BI service stores over 90 days of utilization data. Users who need longer data retention can use Bring Your Own Log Analytics (BYOLA) to store more utilization data.
How do I get visibility into resources of Gen2 beyond CPU time?
Today, customers don’t have visibility through utilization data to the memory footprint of their operations, and cannot know ahead of time whether any of their operations is subject to failures.
How do I use utilization data to perform chargebacks?
On the left side of the utilization report, a bar chart visual displays utilization information between workspaces for the time span of the report. The bar chart visual can be used for chargebacks, providing each workspace represents a different business unit, cost center, or other entity to which chargebacks can apply.
Microsoft’s Power BI helps professionals, including Apple users, better understand their data. Here’s how users with an iPhone, iPad, or Mac can take advantage of all Power BI offers.
The popularity of bestsellers such as Jill Lepore’s “If Then” and Tim Harford’s “The Data Detective” attest to the importance businesses and professionals place on tracking, reporting, and understanding data.
Data is so plentiful that it’s a challenge for organizations to make sense of it. When technical struggles related to data arise, application developers introduce software programs designed to help, and Microsoft is no exception. The Power BI app, available to Microsoft 365 subscribers in both Pro and Premium versions, assists firms in better making sense of the data they collect, including using Apple Macs, iPhones, and iPads.
Take the Metropolitan Museum of Art. The storied museum’s Thomas J. Watson Library, which maintains more than a million volumes and a comprehensive collection of digital resources, recently compiled six years of lending information with additional specially selected data to determine how services and investments match needs. The resulting Power BI data visualizations confirmed the growth of print and digital collection demand while also providing a better understanding of patron and staff activity and the success resulting from migrating informational blog pages to the museum’s site. The resulting Power BI insights proved so compelling that staff chose to publish some dashboards to The Met’s public website.
Professionals employing Apple technologies can leverage the same Power BI capabilities. For example, users can download and install iOS- and iPadOS-specific versions of Microsoft’s Power BI app at no charge; license fees apply to the version used. In addition, Mac users can use Apple Safari to access and manipulate their organization’s information using Power BI.
After a user authenticates by entering credentials for her firm’s Microsoft 365 account within the iPad or iPhone app, she can connect to and model information using self-service data connectors, view reports, leave comments, and share her insights with other team members. A Power BI home page within the app (Figure A) assists with organizing data, provides quick access to frequently accessed content, and offers a centralized starting point. Using the iOS and iPadOS Power BI app, users can also set triggers to receive specific data alerts and manage notifications to enable better keeping pace with data trends and changes as they occur.
Figure A
The iPhone app’s Home page provides quick access to commonly accessed Power Bi elements.
Image: Microsoft
The iPhone and iPad Power BI apps provide, in addition to the Home page, icons for visiting Favorites, Apps, and Workspaces. A More icon, present at the bottom of the Power BI app screen, provides access to Recents, Shared With Me, Samples, and a Scanner, permitting scanning QR codes and uploading images. Don’t underestimate the importance of the Scanning capability, which enables creating QR codes for reports, tiles within the data reporting dashboard, and the ability to view tile information within an augmented reality view. QR codes can be used to simplify direct report access for colleagues. At the same time, users can also leverage barcodes to provide direct access to Power BI reports and data performance metrics for the specific product from which the barcode came.
By being more prominent, the iPad format presents even more information for Power BI users (Figure B).
Figure B
The Power BI iPad app simplifies monitoring data and reports as they’re updated by presenting more information within its display.
Image: Microsoft
Using Apple macOS and the Safari browser, Mac users can navigate to the Power BI site and access favorites and recently accessed information, create new pages, review datasets and goals, and more. The handy navigation bar appears on the left side of the page (Figure C).
Figure C
Mac users can access their organization’s Power BI data using Safari.
Alternatively, Mac users can load Power BI as an app within the macOS-specific Microsoft Teams program. To do so, open Teams, click the More icon from the left-hand navigation menu, click More Apps, highlight Power BI and click the Add button that appears. Once added to Teams, the Power BI app appears as an icon within the navigation bar and, when selected, displays the same information as to its web-browser counterpart. The Power BI app can also be “popped out” of Microsoft Teams by right-clicking the app in the left-hand navigation menu and selecting Pop-Out App, thereby providing Mac users with a seemingly dedicated Power BI app directly on the Mac.
Power BI licensing details
Multiple Power BI licensing options are available. For example, organizations may select Power BI Pro, Power BI Premium (per user), or Power BI Premium (per capacity).
With Power BI Pro, firms pay $9.99 per user per month. The Power BI Pro option is included within the Microsoft 365 E5 plan and provides mobile app access, publishing reports, model size and refresh limits of 1GB and 8 per day, respectively, and maximum storage of 10GB per user, among other features.
Power BI Premium delivers the same features but increases the model size and refresh limits to 100GB and 48 per day, respectively, while adding advanced artificial intelligence and XMLA endpoint capabilities, as well as 100TB of storage. In addition, Microsoft collects $20 per user per month for the Power BI Premium (per user) license.
Firms can opt to license Power BI Premium using a per capacity model, for which pricing begins at $4,995 per month. Using Power BI Premium per capacity licensing, organizations gain access to content without requiring individual per-user licenses and on-premises Power BI Report Server reporting. In addition, the per capacity model increases the model size limit to 400GB, while the refresh rate and maximum storage remain at 48/day and 100TB, as with the per-user option. Other per capacity features include multiple deployment management features and better support for automatically scaling availability (for a separate additional charge) as user and information sets grow, and other virtual server cores are required to process corresponding project data properly.
https://nexumbs.com/wp-content/uploads/2021/10/apple-and-microsoft.jpg578770Nexumhttps://nexumbs.com/wp-content/uploads/2021/03/logo.pngNexum2021-10-31 10:51:122021-10-24 11:00:45How to leverage the features of Power BI when using an iPhone, iPad or Mac
In any data analysis project, whenever we analyze data, always want to find out, some what-if scenarios. For example, what if sales increased by 10% or what if we decreased item cost by 1%.
These what-if analyses can be very helpful for any decision-making process.
Power BI has an AI-driven feature that enables us to implement these what-if scenarios. This is known as What-If Parameters.
In this blog, we are going to explore this functionality with examples.
Get Data
For this case study, I consider the US Superstore dataset from Kaggle.
Let’s start with the Get Data option under the Home tab. As this is a CSV file, select the Text/CSV option from the drop-down list
Select the file named US Superstore data.csv
After selecting the file, data will be displayed in the below format
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Click on Load and save data.
What-if Parameter vs. Power Query Parameter
There is another parameter in Power Query, so please don’t be confuse. What-if parameters are only available in the report and can be used in DAX calculations. Whereas Power Query parameters are available in Power Query Editor only. This parameter changes the behavior of a query.
Properties of What-if Parameter
Go to Modelling Tab → under the What if group, you can find New parameter
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2. Click on New Parameter and below dialog box will open.
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3. It provides below information
Name of the what-if parameter
Data type (Whole number, Decimal number, Fixed decimal number)
Minimum
Maximum
Increment
Default: a value used for the what-if parameter when no value is selected in the slicer.
Add a slicer to this page
Create Discount Range What if Parameter
Create one What if parameter and provide the below information.
Name -> “Discount Range”, Data type → Decimal number, Minimum → 0, Maximum -> 1, Increment -> 0.01
Put Default as 0.01 and click the check box for “Add slicer to this page”.
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4. Click on the “OK” button and two things will be added.
a) Created “Discount Range” table
b) Added one slicer in the page as Discount Range.
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What -if parameter created, but you don’t know how you can use this in your project.
Let us find the application of this parameter.
Application of What-If parameter
Create one calculated measure to use this above parameter in your project.
Create the below measure under the “US Superstore data” table.
Revised Sales = ‘Discount Range’[Discount Range Value]*SUM(‘US Superstore data’[Sales])
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3. Click on Waterfall Chart under Visualization pane.
4. Add Order Date Hierarchy in the Category section. Keep the only Year and Month.
5. Add Category field in the Breakdown section.
6. Add Revised Sales in Values.
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7. After creating any visualization, add some formatting to make it more presentable to the user.
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8. Use the Discount Range slicer to try different values and observe the changes in the chart.
https://nexumbs.com/wp-content/uploads/2021/10/Dashboard-Revenue-Scenarios.png442771Nexumhttps://nexumbs.com/wp-content/uploads/2021/03/logo.pngNexum2021-10-29 10:26:192021-10-31 10:38:07How to Create a What-if Parameter in Power BI
from the upper-right corner to 
