If you ever wanted to try and use capabilities and features provided by Power BI Premium license, now is the time. Starting early Nov 2020 Microsoft Power BI team will be rolling out a new license type in preview. This new license is named: Power BI Premium Per User.
What is Power BI Premium Per User?
In our last post, we touched on two existing Power BI licenses: Power BI Pro and Power BI Premium. If you remember Power BI Premium is a capacity license. If you purchase 1 capacity of this license you can server consumption needs of 450 readers. Read the old post to understand this calculation. But then you have to pay a heft fee of close to $5000 per capacity per month.
Small and mid-size businesses who want to utilize the power of AI, paginated reports, more frequent refreshes, deployment pipelines, and many more features provided by Premium license today got demotivated by just hearing the price.
Power BI Premium per user is a new way to license premium features on a per user basis. With this new license, you get all the capabilities of a pro license along with premium features.
Power BI Pro and Power BI Premium are at the extreme ends of the spectrum. With Power BI Premium per user the gap fills (though only little).
What’s the difference between Power BI Premium and Power BI Premium Per User?
There are some differences. You can check the table below by Microsoft.
But there are still report sharing constraints which are outlined in the table below. Example: If you create and share a report in a workspace marked as PPU, a Pro user cannot view/access that report. So you will need all the users to have PPU license to “view” the report.
What’s the price for the Power BI Premium per user?
There is no official news on the price by Microsoft. However, the good news is it will be free to use in the preview period.
As per official source: “Premium per user will be uniquely affordable and highly competitive among individual user offerings in the industry”
We also don’t know if there will be a min. requirement for the number of PPU licenses.
What’s our thought?
Microsoft clearly says this new license will address the needs to provide a low cost entry point to get access to premium features. However, there will still be more cries than smiles when it comes to users who just need read access. Procuring a Pro or PPU license for them doesn’t make sense even now.
Have more questions?
Head to Microsoft official post on this to know more about scenarios and questions around this.
Microsoft Power BI has some great AI visuals which can provide an in-depth analysis of your data. In our last post we talked about an AI visual – Key Influencer visual. This visual helps in identifying factors that can impact an outcome. In that post, we analyzed what factors influence employee attrition. We also deep-dived into segments and clusters contributing to employee attrition with graphs and charts.
The decomposition tree breakdowns a numerical measure into parts and analyzes what factors cause the measure to be high/low.
From Microsoft documentation:
The decomposition tree visual in Power BI lets you visualize data across multiple dimensions. It automatically aggregates data and enables drilling down into your dimensions in any order. It is also an artificial intelligence (AI) visualization, so you can ask it to find the next dimension to drill down into based on certain criteria. This makes it a valuable tool for ad hoc exploration and conducting root cause analysis.
Let’s take a well known example of employee attrition and understand why attrition is high. From the decomposition tree visual we plan to get answers to the following question:
What causes employee attrition to be high?
At the end of this post you will have an idea of how to use this visual for exploratory and visual analysis, decomposition of values by factors, and how you can use AI splits to dynamically split and understand the next factor for drill down.
Our final output could look like:
We install the latest version of Power BI Desktop, and click on the decomposition tree visual.
You see two input fields “Analyze” and “Explain by”. In the Analyze field we put “Attrition %” and in Explain by we put several other fields say “Overtime”, “Department”, “BusinessTravel”, “MaritalStatus”, “Gender” etc. How to choose these fields in the first place? That’s a tricky question and we will answer this later.
Our decomposition tree when we drag Attrition % looks like:
Attrition % overall is 16.12%. Our next step once we have added our metric is to understand:
Which of the factors cause attrition % to be high?
Which of the factors cause attrition % to be low?
Remember we have dragged several fields in “Explain by” section? Let’s click on the “+” sign next to the Attrition % bar.
You see the fields you have dragged. In addition, you see two more fields – High value and Low value.
Exploratory and Ad-hoc analysis
We begin with exploratory analysis by analyzing Attrition % by OverTime. Attrition % is 30.53% if OverTime is Yes. This means when OverTime is high attrition will be high.
Let’s expand this level and understand when OverTime is Yes then what’s the next factor which contributes to attrition%? Let’s explore Marital Status.
Attrition is high among unmarried individuals and these are the ones who over time. Let’s try adding another level to this analysis, say Department.
Unmarried individuals in the Sales department who over time contribute to 65.31% attrition! We can also verify this number by adding tooltips.
Out of 49 employees in Dept Sales with Marital Status Single and OverTime Yes, 32 of them left the company.
What if we start our analysis, not with OverTime? Let’s pick monthly income as the starting factor
The visual flow is quite different here! Attrition is highest when monthly income is low and in the Sales department when OverTime is High.
With the decomposition tree, you can perform root cause and exploratory analysis by playing with the multiple factors and dimensions. You not only get a deep understanding of what’s happening in your data set, but you can also visually understand the data in a tree format.
We started analyzing the factors based on our domain knowledge and understanding of the dataset. What was our rationale for choosing OverTime as the starting point of our tree?
The decomposition tree comes with another option to split the tree using AI algorithms. Remember we had two more options in our tree “High value” and “Low value”? It’s time to utilize them.
Let’s start with a blank slate and this time instead of selecting OverTime, let’s select “High value”.
As we keep selecting High value at each level of the tree, the algorithm identifies the next level on its own. In the example above the levels chosen were Monthly Income followed by OverTime, Education Field and JobSatisfication. Attrition % is high when monthly income is between 0-2800, and so on.
In AI splits you see a bulb icon next to the level name. Once you hover on the bulb icon you get to see why this level was chosen.
You can also select “Low value”. Once you select the low value you will observe that the factor and analysis changes.
How to choose fields in “Explain by”?
Should we choose AI split or manual split?
How do we choose the fields in “Explain by”?
The best way to start analyzing the tree is using manual split based on the domain context and your understanding of the data. After 2-3 levels of manual split, you can then split the tree further using AI splits and understand the factors responsible for making a metric high or low.
There’s also a smart alternative to this. You can use “Key Influencer Visual” to understand what factors lead to Attrition = Yes. The visual will provide top factors impacting an outcome (attrition = yes), and you can put those factors in “Explain by” section of the Decomposition tree. When you run key influencer analysis on the employee attrition data set you will get the results as explained and shown in the previous blog post.
You can put Age, OverTime, JobLevel, MonthlyIncome, YearsInCompany and others in the Explain by section of the decomposition tree visual and start drilling down the data.
The decomposition tree is a smart visual to breakdown a numerical measure into components. This AI visual aids in root cause and deeper analysis as shown above. You can perform ad-hoc analysis for the problem in question, understand the breakdown of values using manual and AI splits, and combine it with other Power BI AI visuals to strengthen your analysis.
One last note: to get the best of the output and results from this visual, you may want to convert numerical attributes like age, income, etc into categorical values (or bins – Example above: monthly income is broken down into 0-2800, 2800-5000 etc. bins).
PS: AI splits in the decomposition tree comes with two analysis mode: absolute and relative. We will cover this in detail in next blog post.
If you are looking to explore the possibility of applying AI in your dataset or looking to evaluate the use of Power BI in your organization, don’t hesitate to contact us today.
In our last post we talked about Power BI Pro and Power BI Premium. To recap, Power BI Pro is a per use license and is more towards content creation and consumption. On the other hand, Power BI Premium is a capacity license and is more for content consumption.
Rather than assigning a Pro license to every individual in your org, you can assign a premium capacity to a workspace to support large number of content viewers.
In this post we will tackle another Power BI offering – Power BI Embedded.
Power BI Embedded
Power BI Embedded is a Microsoft Azure service that lets independent software vendors (ISVs) and developers quickly embed visuals, reports, and dashboards into an application. This embedding is done through a capacity-based, hourly metered model.
Power BI Embedded is an offering by Microsoft where you can embed Power BI visuals, reports, and dashboards in a custom application or in associated Microsoft Services like Teams or SharePoint Online.
How does Power BI Embedded look like in reality?
Ok, here’s a screenshot of a Power BI report embedded inside a custom application. By custom application I mean an application which is not app.powerbi.com. It can be a plain vanilla website or a WordPress website or can be a heavy application with Reporting and Analytics section.
In the screenshot below, the sections highlighted in red are part of the custom application. The “SALES PERFORMANCE REPORT” or the part highlighted in green is the Power BI report securely embedded in the application.
You can embed a visual, report, dashboard and Q&A. We have used “report” as a general content for embedding. But the description apply to any of the contents.
How can I embed a Power BI report?
There are 3 ways to embed a Power BI report.
Publish to web. Simplest (and not secure) way of embedding is publishing your Power BI report to web for public access. Note: Anyone with the URL will have access to your report.
No-code Embedding – Simplest and secure. This approach gives you a secure URL to the Power BI report which you can put in your application. However, this will prompt you for Org authentication.
What licensing do I need to support Power BI Embedding?
Now, that’s a tricky question. For embedding you can choose – P SKU, EM SKU or A SKU.
The licensing to go for really depends on your specific scenario. The general answer to choosing the SKU is “where” the content will be consumed.
If the Power BI content will be consumed in a custom application then choose A SKU**
Choose EM SKU if the Power BI content will be consumed in Teams or SharePoint online (SPO).
Choose P SKU if the Power BI content will be consumed in a custom application or Teams or SPO.
**You can even choose a P SKU if you are an enterprise or a Large ISV.
The P SKU is an umbrella SKU which not only gives embedding capabilities but additional feature sets including large read users, AI features, and other enterprise features.
Typically, enterprises go with P SKUs.
How are P, EM and A SKUs different in terms of performance?
Here’s a quick summary of each of the SKUs node performance:
So an A4 node is same as a P1 node in terms of performance.
It is generally suggested to start with A1 to test and benchmark your capacities, and then take necessary steps to increase the capacity.
Is Power BI Embedded free to use?
No. For production workloads you have to choose from either of the licensing types. For dev workloads, yes you can embed without purchasing a capacity. However, you may hit the token limits and reports may not render.
Before investing your budgets in a modern BI tool for your organization, we strongly advise to evaluate your BI vendors security and architecture. Whether the tool is Power BI, Tableau, Qlik or Looker, each of these tools provide a cloud BI solution for your needs.
You have cloud and on-premise versions. Using the cloud version offers several known advantages. However, data security becomes the key. There are several questions that might be bothering you.
Is my data secure?
Where is my data stored?
What security options and best practices does the vendor implement?
How is the data movement?
Is the data encrypted? What all is encrypted?
Does this sound like you?
If you are looking for answers to above questions or evaluating Power BI as your go to modern Enterprise BI tool, I invite you to read Power BI security whitepaper which talks about Power BI security and architecture in detail.
Power BI is a SaaS platform by Microsoft hosted on Azure. It uses Azure services for its operation. There are Web Front End clusters and Back End clusters.
Front End cluster
The frontend cluster (WFE) is responsible for initiation and authentication to the Power BI service, sending static files and content.
Back End cluster
The Back-end cluster role comes into play once the authentication is done. This cluster is responsible for data, storage, visualization, connections, refresh, and other user interactions etc.
The Back End cluster is the heart. If you consider your data as your asset, then the Back End cluster is a critical asset.
You should particularly focus on items to the left of the dotted line above and items to the right of the dotted line. A request to get data, dashboards or reports goes to “Gateway Role” only. This Gateway Role decides where to route the request.
Snippet from the security paper:
The Gateway Role acts as a gateway between user requests and the Power BI service. Users do not interact directly with any roles other than the Gateway Role.
Important: It is imperative to note that only Azure API Management (APIM) and Gateway (GW) roles are accessible through the public Internet. They provide authentication, authorization, DDoS protection, Throttling, Load Balancing, Routing, and other capabilities.
The dotted line in the Back-End cluster image, above, clarifies the boundary between the only two roles that are accessible by users (left of the dotted line), and roles that are only accessible by the system. When an authenticated user connects to the Power BI Service, the connection and any request by the client is accepted and managed by the Gateway Role and Azure API Management, which then interacts on the user’s behalf with the rest of the Power BI Service. For example, when a client attempts to view a dashboard, the Gateway Role accepts that request then separately sends a request to the Presentation Role to retrieve the data needed by the browser to render the dashboard.
Top questions asked by customers
Where is my data stored?
The data that you upload along with Power BI Report (PBIX) is stored in Azure Blob Storage. The metadata – data about dashboards, reports, refresh cycles etc. is stored in Azure SQL Database.
The data is stored in the region same as the Power BI tenant’s region.
In the Power BI service, data is either at rest (data available to a Power BI user that is not currently being acted upon), or it is in process (for example: queries being run, data connections and models being acted upon, data and/or models being uploaded into the Power BI service, and other actions that users or the Power BI service may take on data that is actively being accessed or updated). Data that is in process is referred to as data in process. Data at rest in Power BI is encrypted. Data that is in transit, which means data being sent or received by the Power BI service, is also encrypted.The data at rest and in transit is encrypted.
Source: Power BI Whitepaper
Is Power BI Pro secure?
Power BI Pro is a shared environment. The Frontend and backend clusters could be shared between customers. Azure Blob Storage and Azure SQL Database could be shared between customers.
Is Power BI Premium secure?
When you initiate a Power BI Premium subscription, behind the scenes the back-end clusters are deployed to dedicated VMs. These VMs are dedicated to you and should not be shared between customers.
What happens when I login to app.powerbi.com?
Check this section in the whitepaper to know what happens behind the scenes when you try to access app.powerbi.com
All Power BI features in one page?
Check out this blog to see all Power BI features in one page!
Power BI is a great Modern BI tool. When evaluating Power BI for Enterprises, we walk them through the architecture and security implementations in Power BI. This boosts enterprise customer confidence to take next big step in modernizing their reporting and analytics.
Don’t hesitate to contact us today if you are looking for Power BI Enterprise deployment or want us to evaluate Power BI as your go to modern Enterprise BI tool.
Power BI has seen viral growth. It is one of the industry leaders in BI and Analytics Platform. One of the reasons for such growth is its integration with existing Microsoft investments. We would say, it’s easier and cost-effective to get started with Power BI.
Following points are a must read if you are looking to migrate to Power BI
First and foremost, migration to Power BI needs a change in your mindset. You have been using your old tool for quite some time now. You expect Power BI to mimic its functionality and behavior? No, it may not. Power BI is a Modern Enterprise BI tool. With modern approaches to data modelling, data consumption, sharing and governance, Power BI pushes you to think beyond traditional tools.
Don’t Mimic Excel
For laymen, Power BI is Excel++. They expect to modify a “cell” in Power BI and hope to see changes reflected in Power BI. Wait, wait, wait! Power BI is not Excel nor a replacement for Excel. Power BI gives much more power to data extraction, modelling, and data storage. Don’t expect Power BI to work like Excel. Excel is best suited for calculations, manipulations, and tabular/visual reporting. Power BI is a modern BI tool with storage, compute, data flows, AI, governance – well integrated within the platform. Don’t worry, you can still use Excel with Power BI with “Analyze in Excel” feature. For enhanced functionality, you have Power Apps, Power Automate, etc.
Model driven tool
“Can I fire a dynamic SQL query based on filter selections and user login in Power BI”? Charting libraries use this concept quite often. Please note: Power BI is a model driven tool. There is a model behind which powers the visualization and analytics. You need to start thinking about models and relationships when working with Power BI. You can import the data in Power BI or connect directly/live with supported data sources. Once done, you can slice and dice they way you want.
In Active development
Power BI is a tool that is in active development and growth. There can be some features that are not yet available, but that doesn’t mean you will stop leveraging the power of this modern tool. Power BI has a monthly release cadence and they also publish a roadmap so you know what’s coming in future releases.
They just announced some fantastic updates in MBAS 2020.
A Product for all size needs
Power BI is a suite of products.
Power BI Desktop for authoring and creating reports,
Power BI Online for data distribution, consumption, governance, and management,
Power BI Embedded for embedding in your website,
Power BI Premium for enterprise needs,
Power BI Report Server for on-premise needs,
Power BI Report Builder for paginated/tabular reports (SSRS types reports) and
Power BI Mobile for on the go needs.
Plus, integrations with Excel, SharePoint, Teams, Power Apps, Power Automate, AI, Azure Analysis Services, and many more etc.
We can pickup one or more tools depending on your needs. Power BI has definitely come a long way. Many organizations are taking advantage of this modern BI tool. Why not you?
How to get started?
Here are simple steps you can take to get started on your journey to migrate to Power BI.
Get your current data estate and BI systems audited