Our first impression of Tableau – intuitive, powerful, beautiful

#PowerBI experts, Crush on #Tableau

Power BI and Tableau has been ranked as leaders in Gartner’s Magic Quadrant for Analytics and BI 2020. It becomes critical for businesses to choose between one of these solutions for their analytics and BI workloads.

Of late, we have been receiving a lot of questions and interests in choosing BI tools. Recent trends show that companies are open to Power BI or Tableau as long as their needs are met within budget.


We are open to choosing and suggesting BI tools to our customers. We decided to give a try to Tableau.

Our first impression of Tableau

Tableau is intuitive. Tableau is quick. Table is powerful. Tableau is beautiful.

Tableau’s power is its data visualization capabilities.

You need a dual axis chart with bars and lines? You got it.

You need a dumbell chart? You got it.

You need advanced analytics? You need greater control over tooltips? You need annotations?

You got it!

Looks like Tableau was built ground up with data visualization in mind. And, it’s correct. Tableau founders were from graphics and visualization background.


How does it compare with Power BI?

After our hands on with Tableau we can say Power BI visualization capabilities though familiar, are limited. You have the same decade and century old charts.

You can be creative with visuals but then you need to learn Typescript and Node.js. You can create new and advanced charts but development and learning curve is high.

How about modelling capabilities?

Power BI excels in data modelling capabilities. DAX and multi-dimensional concepts are inbuilt in Power BI.

Tableau lacks much of these. Minimal multi-dimensional support, no functional language like DAX. Tableau relies on calculation scripts, LOD etc.

How about Dashboards and Reports on canvas?

Tableau has concept of Sheets and Dashboards. Power BI has concept of Reports and Dashboards.

We feel Power BI wins here as you have greater control over the layout and structure of your reports. You can create Business dashboards quite easily in Power BI.

What about Publishing options?

With Tableau you can publish to a Tableau server or Tableau online. Same with Power BI.

However, Power BI service (or Power BI online) though looks cluttered sometimes, is quite powerful and feature rich. Navigation can be confusing. It has a concept of workspaces.

Tableau online is clean and has simple interface. Admin capabilities and options look limited. It has a concept of projects. Great UX.

What about cost?

To a large extent Power BI wins here. Power BI Desktop is free. Power BI Online is free for personal use. This makes Power BI quicker to adopt and penetrate within your org.

Tableau unfortunately is not free. It’s costlier than Power BI. Though Tableau has a free version called Tableau Public, its functionality is limited.

Note: We need to evaluate cost in a larger scheme of things keeping view of number of creators, number frequent and occasional users.

How is the support for developer tools?

Microsoft is known for developing products for extensibility. Power BI wins here with APIs to manage everything you need. Power BI lacks APIs for designer and modifying models.

Tableau has some support for tools but it’s limited.

What do you recommend?

Power BI and Tableau, both are great tools. However, recent job trend shows greater demand for Power BI developers.

To sum up: Power BI is a great end to end BI tool. Tableau is a great visualization tool.

We recommend to check your existing BI investments, and BI and analytics needs. Based on this and your budget, take a call.


Given high demand for both the tools, we are working on creating a comprehensive guide comparing Power BI and Tableau. We will cover in detail their BI capabilities, Data Integrations, Enterprise support, APIs and costs with screenshots from both the tools.

Join our list to be the first one to know when the guide is available.

Do you want us to evaluate which BI tools fit your business needs? Contact us now.

Gartner Magic Quadrant for Analytics and BI Platforms 2020

Business Intelligence tools have been in market since years. What has now started differentiating them is:

  1. Support for Enterprise reporting needs – large datasets, on-prem and cloud, data governance, security, agile dev cycle
  2. Augmented analytics capabilities – Machine Learning capabilities and AI assisted insights generation and explanation

This Magic Quadrant will help data and analytics leaders complement their existing solutions or move to an entirely new vendor.

Directly from Gartner:

Augmented capabilities are becoming key differentiators for analytics and BI platforms, at a time when cloud ecosystems are also influencing selection decisions

Here’s what Gartner Analysts think in terms of numbers:

By 2022, augmented analytics technology will be ubiquitous, but only 10% of analysts will use its full potential.

By 2022, 40% of machine learning model development and scoring will be done in products that do not have machine learning as their primary goal.

By 2023, 90% the world’s top 500 companies will have converged analytics governance into broader data and analytics governance initiatives.

By 2025, 80% of consumer or industrial products containing electronics will incorporate on-device analytics.

By 2025, data stories will be the most widespread way of consuming analytics, and 75% of stories will be automatically generated using augmented analytics techniques.


Here’s presenting the 2020 Magic Quadrant for Analytics and Business Intelligence Platforms.

Magic Quadrant for Analytics and Business Intelligence Platforms
Magic Quadrant for Analytics and Business Intelligence Platforms – 2020

Microsoft (Power BI), Tableau, Qlik and ThoughtSpot are leaders in this space. How did this look like last year?

Magic Quadrant for Analytics and Business Intelligence Platforms – 2019

How about 2015 vs 2020? Lot has changed since then. The Leaders space was crowded back then.

Magic Quadrant for BI tools – 2015

Here’s the direct link to the full report on Gartner’s site with each vendors strengths and cautions in detail along with 15 Critical Capabilities of an Analytics and BI Platform.


For 13 consecutive years, Gartner has recognized Microsoft as a Magic Quadrant Leader in analytics and business intelligence platforms. When they reference Microsoft, they are referencing to the Power BI platform.

Looking to adopt Power BI in your organization? Contact us for a free consultation on how Power BI can help you realize your modern BI vision.

Get in touch now!

Power BI Premium or Power BI Pro – the answer is here!

Power BI comes with multiple licensing model

  1. Power BI Pro
  2. Power BI Premium
  3. Power BI Embedded
  4. Power BI Free

In this post we will cover Power BI Pro and Power BI Premium licensing model.

Which licensing model to go with is determined by following three factors:

  1. Cost
  2. Number of users (creators, viewers, occasional viewers)
  3. Features required

The first two factors are the most critical in deciding the licensing model.

It’s a choice between multiple Pro licenses or multiple Premium licenses.

A Power BI Pro is a per user license currently costing around $10 per user per month, while Power BI Premium is a capacity license currently costing around $5000 per capacity node per month.

Yes, the cost difference is huge. But, wait, there are lots of things hidden in that $5000.

  1. Power BI Premium is a capacity license. It can support 450 users report viewing needs (see example below)
  2. Power BI Premium is for content consumption rather than content creation
  3. Large number of external readers (out of org users with no Power BI license)
  4. AI, Paginated reports, XMLA read/write and many other features

What does that mean?

If you want to create, author and publish reports, you definitely need Power BI Pro licenses. You cannot go away with that. Whether to go with Power BI Premium or not, it depends.

Say, if you have 500 users in your org and out of 500 users

  1. 50 users will be creating content
  2. 200 users will be frequently accessing the content
  3. 250 users will be occasionally accessing the content

Then, you require

  1. 50 Power BI Pro licenses
  2. 1 Premium capacity node

With the premium capacity node we can serve the “consumption” needs for 450 users.

How did we come up with that conclusion? A simple Power BI Premium calculator is available to help us decide number of licenses (link below).

But, say your org has 100 users with 50 creating content and 50 viewing, it’s recommended to go with 100 Pro licenses (total cost $1000 per month) than a premium capacity node unless you need additional features like AI, external readers etc.


Power BI Premium vs Power BI Pro – Which licensing model should I choose? The answer is here!


If you are still not sure of the licensing model or worst, if you are not sure if Power BI is fit for your organization’s BI needs then you may request a free consultation.

You may fill the form below or directly setup a call

Or, fill up this form and we will get back to you with time slots within 12-24 business hours.

Notes:

Power BI Premium Calculator: https://powerbi.microsoft.com/en-us/calculator/

Power BI premium also comes with additional feature sets including AI, Incremental refresh, Power BI Report Server, Paginated (SSRS types) reports, XMLA read/write and others – or better to say Enterprise features.

If you need a quick comparison between Power BI Pro and Power BI Premium feature sets, please check this table provided by Microsoft. (Click the image to view the entire table)

https://powerbi.microsoft.com/en-us/pricing/#powerbi-comparison-table

Refresh Power BI report page every min. and show on a TV

This question has been asked multiple times in forums, blogs and in Power BI community.

How can I refresh my Power BI report every min and show it on a TV full-screen?

This is a lovely scenario where you want to show Power BI report with metrics, business performances, team performances etc. on a public display. May be on a TV in a hallway or in Factory Control rooms!

But, how do I do this?

It’s quite simple to setup!

(1) Make sure your data is refresh-able live. Either through direct query to a supported source (SQL etc.) or live connection to Analysis services.

(2) In your report URL in Power BI Service, append ?chromeless=1

This setting will open your report in full screen mode.

(3) Download and install a Google Chrome Add-in – “Super Auto Refresh Plus”

https://chrome.google.com/webstore/detail/super-auto-refresh-plus/globgafddkdlnalejlkcpaefakkhkdoa

(4) Setup the Add-in to refresh your report page every X mins. You want 10 seconds? You are covered!

And you are set to go.

A simpler way to refresh your report page every min and show it on a display!

Questions?

-Ranbeer

(@ranbeerm)

HubSpot to Power BI

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

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

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!

This post talks about two general approaches to copy data to Power BI from online services.

Approach 1: Use Power Query 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, 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 you want to reuse the data from these services.

Questions to ask:

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 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.

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.

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 online services data!