Power BI Embedded Licensing

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.

Microsoft

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.

  1. 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.
  2. 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.
  3. Custom Embedding using JavaScript SDK. This gives you full power of embedding capabilities. You can read more about how to embed using JavaScript SDK in our other blog post.

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:

Image source: Microsoft

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.

Quick URLs for further reading

Power BI Embedded Capacity: https://docs.microsoft.com/en-us/power-bi/developer/embedded/embedded-capacity

Developer Samples: https://github.com/microsoft/PowerBI-Developer-Samples

Power BI Embedded Playground: https://microsoft.github.io/PowerBI-JavaScript/demo/v2-demo/index.html


I hope this post provides some understanding on Power BI Embedded, licensing and consideration for choosing this type of offering.

Next steps?

If you have any questions on this or want to explore Power BI Embedded for your organization, do contact us today.

Power BI Get Data APIs

Tons of questions on how can we copy data from Facebook Ads or HubSpot or Google Analytics or any other SaaS platform or APIs to Power BI.

There are a couple of reasons why you want to analyze data from multiple sources with Power BI.

Why should I care?

Say you want to analyze how much traffic and number of leads (CRM) are generated by spending on Ads on Google and Facebook. And, how many of them actually purchase (Stripe or PayPal)?

You can go to each of these service providers dashboards and get answers to your questions, one by one. Or, you can copy data from these providers into a single system say Power BI and analyze data together. Which one do you think will give you a clear business picture and with much less overhead?

Clearly the Power BI one!

Power BI provides data connectors to a good number of services already. Google Analytics, Facebook Page, MailChimp, SalesForce, MixPanel etc. But there are a number of sources for which you do not have data connectors yet – HubSpot, Facebook Ads, Instagram Ads, LinkedIn Ads etc.

Update (April 30): We have created a list of popular Power BI custom data connectors. The list includes connectors to HubSpot, Zendesk Support, Facebook Ads, Instagram Ads, LinkedIn and more. Check here.

Of late I have been seeing a lot of requests to copy data from HubSpot to Power BI!

What are my options?

This post talks about two general approaches to copy data to Power BI from SaaS platforms and APIs.

Approach 1: Use Power Query (within Power BI) to get data from Online Services (through REST APIs), model, and visualize data in Power BI – Self Service, Simple, Less cost

Approach 2: Setup data factory pipelines using say Azure Data Factory or setup Azure Functions, copy data to a database/data warehouse and use this data layer to visualize in Power BI – Enterprise, More control on data, Involves several components

Which approach to go with will depend on how frequently you want the data pulls and how you want to reuse the data from these services.

How should I decide?

Questions to ask:

Question 0: How frequently you want to pull data? Every 15 mins? Every 2 hours? Every day?

Question 1: Are you going to use the data only in Power BI/Excel and only for visualization and analysis?

Question 2: Are you going to use the data in another application or going to reuse that data for Machine Learning or other use cases?

Question 3: How big is your data?

If your data pull requirements are every 2 hours or so and is small* and does not have to be used outside of Power BI/Excel and the purpose is only visualization and analytics – go with Approach 1.

Else go with Approach 2.

Approach 1 is quick to implement and will incur a less overall cost.

Approach 2 could take time to implement and has several other components than just Power BI (read on).

Approach 2 also provides you ability to pull incremental data. While in Approach 1 (Pro users) you have to pull full data every time.

Update Feb 2020: You can now perform incremental refresh in Power BI Pro.

*Note 1: I have seen Power BI experience getting degraded if your model size becomes more than 300 MB.

Help me decide?

Contact us if you need assistance with similar data movement activities from your SaaS platforms and APIs.

Examples to showcase how to use Approach 1.

You can go with either “Get Data” way or a Custom Connector way. I will show steps for “Get Data” way to connect to HubSpot (CRM).

Step 1. Go to “Home” tab in the Power BI Desktop ribbon, select “Get Data->Web”

Get Data -> Web

Step 2: Select “Advanced” radio button and put API details. The screenshot below shows examples for connecting to HubSpot ‘Companies’ API endpoint.

Connect to HubSpot Companies API endpoint

Step 3: Apply transformations using Power Query

Transform JSON data to tabular format using Power Query transformations.

Step 4. Start visualizing!

Sales Pipeline Report from HubSpot data developed by us.

Play with Sales Pipeline Report LIVE

Examples to showcase how to use Approach 2.

Here we take Azure Data Factory to pull data from Google Analytics API.

Note: In the example below “FlattenJSON” is an Azure Function to simplify complex JSON returned by Google Analytics API.

Step 1: Setup data pipelines using say Azure Data Factory and push data to a database/data warehouse

Azure Data Factory v2 data pipelines to copy data from Google Analytics to Azure SQL

Step 2: Connect to the database using Direct Query Approach in Power BI

Direct Query to connect to Azure SQL

Step 3: Start visualizing!

Google Analytics data visualized by us using Approach 2

I have seen customers going with Approach 1 almost always since this saves time and cost. But this approach may require a gateway for data refreshes.

Which approach have you used in similar scenarios? Let me know

Thanks,

Ranbeer M

Note 2: Power BI has dataflows which may replace Azure Data Factory in scenarios above.

Note 3: Power BI team is also working to expose the data model behind the scene as Analysis Services. You can then query the data through SSMS. That feature should come out in preview in Feb 2019. (This date is from Microsoft Power BI blog/website)

This is available now. Check here.

Note 4: Power BI team has released AI features in private preview so you can apply ML techniques to your data in Power BI! More on that in this and this blog post.

Note 5: You may contact us if you need similar data movement and analytics for your Saas platforms and APIs!