Data Analytics – The Power BI way

In my previous articles related to BI, we have explored extensively on Tableau and SAP Business Objects. While I continue the series, it would be unfair if I don’t cover another ’emerging’ solution – Microsoft Power BI (in fact it is a market leading BI solution already, refer to my post for 2017 BI trends here Gartner Magic Quadrant for BI and Analytics)

Those who are familiar with Tableau will find themselves home with Power BI in many ways. However Power BI is unique in terms of features, the publish options, pricing and visualization options such as custom visualizations.

Power BI was completely cloud based solution until recently – i.e, until the release of Power BI Report Server in this month (June 2017).  In the cloud based solution, you have to publish your visualizations to Power BI Service on cloud. You have alternative to Power BI desktop for development in the form of Power BI Service Web Interface which provides similar options for creating and customizing visualizations.

I have sketched a high level cloud based (Power BI Service) implementation architecture below  connecting to on-premises database to understand the different components better.

Power BI Architecture

Implementation architecture using Power BI Service on cloud connecting to on-premises database

The implementation architecture below shows the on-premises solution using Power BI Report Server. In this implementation, development and publishing do not require cloud. Note that the development require installation of custom release version of Power BI Desktop (Power BI Desktop optimized for Power BI Report Server)

 

PowerBI Architecture_OnPremise

On-Premises implementation architecture using Power BI Report Server

In terms of connectivity, Power BI can connect to almost every data source. However the type and location of data should decide your design and type of connectivity.

On-Premises Database connectivity from Power BI Service : If you have an on-premises database, Power BI service allows the connectivity using gateways. The options are (a) data imported to Power BI service or (b) use direct query or live connections. We will explore these implementation models in detail in the upcoming articles.

PowerBI_DataSourcePowerBI_DataSource1

Custom Visuals : This is really great feature that Microsoft lets Power BI developers to create and publish their custom visualizations which can be added to your visualization tray and integrate with your reports/dashboards. Thanks for the support to creativity from developer community.

R Integration to Power BI :  Similar to Tableau R integration, we can connect to R for performing complex predictive analysis.

PowerBI_R_Integration

I will cover R integration details and many more in upcoming posts.

Data Analytics using Tableau – Trends & Trend Lines

In my previous blog, I had posted a bar chart showing declining trend in sales of a company over the years. If you notice, it had a trend line to aid visual analytics.

graph-1

Another example given below shows profit trends by increase in sales for each category.

Tableau_Trend_Lines

Trend lines are great visual tools for quick analysis. In the above diagram, its very easy to judge that the increase in sales for Supplies and Tables does not help increasing profit. The same judgement could not have been derived that easy from the clustered circles if the trend lines were not present. The steps to add Trend Lines are explained below.

I have created a scatter plot for Sales vs Profit using the Global Superstore database. Notice the “analytics” tab highlighted below.

Tableau_Trend_Lines1

Drag ‘Trend Line’ from the options to the visualization area and choose the line type. In this example, I have selected Linear model.

Tableau_Trend_Lines2

Tableau_Trend_Lines3

Additional options are available at (Right click -> Trend Lines-> Edit Trend Lines). For example, you can choose to show only one line (uncheck show trend line per color) and view for each category interactively for focused view/analysis as shown below

Tableau_Trend_Lines4

 

Data Analytics using Tableau

Though we discussed extensively about SAP Business Objects w.r.t business intelligence tools, I could not get a chance to write about Tableau visualizations till now. Not a great thing considering that my experiments with Tableau started way back in 2012 with Tableau version 7.0 (it wasn’t as popular as today, but it was clearly emerging as a leader). Tableau is one of the best visualizations tool that I have experienced and you can’t stop admiring its performance (thanks to in-memory processing of data), interactivity and analytics options (trends and forecasts).

Starting with a few visualizations from my PC. We will explore specific features and steps in later blogs.

Lets analyze data of a company (data source: Local SQL Server database). As you see the sales and profits are declining. I have added a trend line for its sales. This shows a consistent fall and its time for the company to do something serious to revive the business, isn’t it?

graph-1

Sometimes a different visualization is what the need of the hour to convey the same data. How about a packed bubble visualization with the sizes corresponding to Yearly sales. Note that the data is categorized further by Divisions (company locations)

graph-2

And my favorite Geo Maps

graph-3

We will dig into its analytic features and Tableau Online in the upcoming posts.

Bisiness Intelligence & Analytics – Do you have the right tool?

It was long due from my end to allocate some space in my blog series for one of the area that I have explored extensively over the last few years – Business Intelligence and Analytics. It was exciting journey along with the evolution of BI using software solutions such as SAP Business Objects, Microsoft SSRS, SSAS, TIBCO Spotfire and Tableau. My experience with these different BI solutions helps me to compare and evaluate the capabilities of these tools against the business requirement and identify the right solution.

If you work with data and having difficulty in delivering solutions to the requirements, you should sit back and look for answering the questions below:

  • Am I using the right Business Intelligence tool for my requirement?
  • Are the features in the tool inadequate?
  • Are the BI tools/reports inefficient or slow?
  • Is my tool too complex to learn or to develop solutions?
  • Are my users facing difficulty in interpreting the data visualizations presented?
  • Can my organization afford the desired BI solution? What are alternatives?

Define the problem areas with questions like these and it will start guiding you to course correct the current approach that you use. And these questions are equally important even when you are at a new requirement and subsequent design and selection of BI solution. I will go through some of these key criteria in the upcoming articles. Filter using the tags given here.