PASS Business Analytics Conference Keynote Day #1


In this post, I’ll summarize the PASS Business Analytics Conference’s Keynote Day #1:

The structure of the Keynote:

PASSt Business Analytics Conference

One of the NEW challenges that Data Pros face today is complexity involved in building a BI solution. Following slides nicely represent the challenge from the Tools standpoint:

pass business analytics conference keynote hadoop

Image Courtesy:

Microsoft’s Goal is to SIMPLIFY the above situation

NEW Tools:

> Data Explorer (Excel add-in)

> Power View in Excel 2013

> Geo Flow

Key Take away from the demo’s was:

Power View is a great tool that you could use to extract insights from data.

E.g. Insights about Music Charts from Germany:

Now combine the power of Power View w/ the new capabilities like Data Explorer that let’s you find, combine & refine data via Data Explorer.

In the Demo, they combined data in hadoop w/ data in relational sources. This is Powerful!

And Also

The Preview for GeoFLow in Excel was announced!

They had a great demo on a pretty big touch device:


Sorry for the poor image – but imagine a touch device of that size w/ an interactive data visualization that has 3D geo maps!


They had a nice message at the end of the keynote:


Data Reporting ≠ Data Analysis


One of the key thing I’ve learned is importance of differentiating the concepts of “Data Reporting” and “Data Analysis”. So, let’s first see them visually:

data analysis and data reporting

Here’s the logic for putting Data Reporting INSIDE Data Analysis: if you need to do “analysis” then you need reports. But you do not have to necessarily do data analysis if you want to do data reporting.

From a process standpoint, Here’s how you can visualize Data Reporting and Data Analysis:

data analysis and data reporting process

Let’s thing about this for a moment: Why do we need “analysis”?

We need it because TOOLS are really great at generating data reports. But it requires a HUMAN BRAIN to translate those “data points/reports” into “business insights”. This process of seeing the data points and translating them into business insights is core of what is Data Analysis. Here’s how it looks visually:

Data analysis Data Reporting

Note after performing data analysis, we have information like Trends and Insights, Action items or Recommendations, Estimated impact on business that creates business value.


Data Reporting ≠ Data Analysis

Resource: 12 recorded sessions from the 24hop business analytics edition are online! #passbac #msbi


Recently, PASS hosted a 24hop business analytics event:

And now, the 12 one hour sessions ranging from data visualization, predictive analytics to Big Data are online for you to watch! They also serve as “Trailer” for what you can expect at the PASS Business Analytics conference!

Here’s the URL:

And I was following some of these sessions live on the event day – and I can tell you, these sessions are great resources!

Also, I participated in the twitter contest (by Microsoft BI) that was happening along w/ the event – and this is what I got for my win!

24 hop twitter contest prize

hoodie w/ embedded earphones!

That’s about it for this post. Enjoy the recordings!

Statistics 101: Nominal, Ordinal, Interval, Ratio Data


If you work with any statistical analysis tool, sometimes you may have run into configuring the data into either of these following categories: Nominal, Ordinal, Interval, Ratio

Here is what each term means:

NominalSimply names or call them set of charactersExample: Full name, fruits, cars, etc
OrdinalNominal + They have orderExample: Small, medium, big
IntervalOrdinal + the intervals between each value are equally splitExample: temperature in Fahrenheit scale:10 20 30 etc

Note that 20F is not twice as cold as 40F. So multiplication does not make sense on Interval data. But addition and subtraction works. Which brings us to next point: Ratio

RatioInterval + multiplication makes senseWeight: 60KG, 120KG.120 KG = 2 * 60 KG

I hope the examples are of help when you are working with statistical analysis tools and need to categorize the data.

Examples of Machine Generated Data from “Big Data” perspective:


I just researched about Machine Generated Data from the context of “Big data”, Here’s the list I compiled:

– Data sent from Satellites

– Temperature sensing devices

– Flood Detection/Sensing devices

– web logs

– location data

– Data collected by Toll sensors (context: Road Toll)

– Phone call records

– Financial

And a Futuristic one:

Imagine sensors on human bodies that continuously “monitor” health. How about if we use them to detect diabetes/cancer/other-diseases in their early phases. Possible? May be!

Interesting Fact:

Machine can generate data “faster” than humans. This characteristics makes it interesting to think about to analyze machine generate data and in some cases, how to analyze them in real-time or near real-time

Ending Note:

Search for Machine Generated Data, you’ll be able to find much more, it’s worth reading about from the context of Big Data.


Neologism is the new challenge for IT professionals, Here’s why:


What is Neologism?

Neologism means The coining or use of new words – And I believe it’s one of the challenge faced by IT professionals. Nowadays, we put our time & energy trying to get head around “new terms/words/trends”.

Let’s take couple of example(s):

Sometime back, we had cloud computing. Nowadays, its Big Data; In my mind – Big Data has been coined to mean following technologies/techniques under different contexts:

Big Data Unstrucutred External Text Public Data

Note: The above image is just for illustration purpose. It does not comprehensively cover every technology that is now called “Big Data”. Feel free to point it out if you think I missed something important.

And Neologism is challenge because:

1) Generally, it’s a new trend and there is little to no consensus on what does it “Exactly” mean

2) It means different things in different context

3) Every person can have their own “interpretation” and no one is wrong.

4) It’s a moving ball. The definition used today will change in future. So we always need a “working” definition for these terms.

Now, Don’t get me wrong, It’s fun trying to figure out what does it all mean and trying to gauge whether it matters to me and my organization or not! What do you think – as a Person in Information Technology, do you think that Neologism is one of the challenges faced by us? consider leaving a reply in the comment section!

Related Articles:

Want to learn about BigData? read Oreilly’s Book “Planning for BigData”

Quote for Big-Data / Data-Science/ Data-Analysis enthusiasts:

Who on earth is creating “Big data”?

Examples to help clarify what’s unstructured data and what’s structured?

Things I shared on Social Media Networks during Noc 12 – Dec 31 (2012)


Big Data: The Coming Sensor Data Driven Productivity Revolution

Check out some nice getting started tutorials at beyondrelational site:

Complexity is your enemy. Any fool can make something complicated. It is hard to make something simple – Richard Branson

— via Paras Doshi – Blog

The success of companies like Google, Facebook, Amazon, and Netflix, not to mention Wall Street firms and industries from manufacturing to retail and healthcare, is increasingly driven by better tools for extracting meaning from very large quantities of data,” says Tim O’Reilly

— via Paras Doshi – Blog

Nice collection of about 20+ videos around the topic of “Data Science”:

Nice collection of videos by Berkeley school of information: #Information #Data

Just found Facebook’s data team’s page:

via V Talk Tech – A Parth Acharya Blog – Nice HeatMap of stocks!

what’s the biggest fear about cloud computing? via Windows Azure

Resource: Presentations from the Sentiment Analysis Symposium

If I switched to the newest “holiday” theme on WordPress, this is how it would look:

Nice! Code School now has R programming language! I have been playing with R for a while now and definitely want to learn more – here’s the link to learn R:

Interesting tool from Google to optimize and analyze web page speeds:

Performed #sentiment #Analysis on #starbucks twitter data using #R ! It was fun!

In 2002: The Data Warehousing Institute estimates that data quality problems cost U.S. businesses more than $600 billion a year. And of course, over the past 10 years, this number would be bigger.

Reading: Business Analytics vs Business Intelligence?

Big data is a nickname for the recent increase in largely external and unstructured business and consumer information. How are businesses across industries harnessing traditional enterprise information management functions and systems to translate big data into useful business intelligence?

For business analytics professionals: 12 webcasts on Jan 30th 2013 #sqlpass #analytics #24hop

Some nice insights about how to build an Internet platform, from the founder of Zipcar:

Let’s connect and converse on any of these people networks!

paras doshi blog on facebookparas doshi twitter paras doshi google plus paras doshi linkedin

There’s been a growing interest in Hadoop & Big Data, Here’s the Proof:


I like to keep an eye on Technology Trends. One of the ways I do that is by subscribing to leading magazines for articles – I may not always read the entire article but I definitely read the headlines to see what Industry is talking about. during last 12 months or so I have seen a lot of buzz around Big Data and I thought to myself – It would be nice to see a Trend line for Big Data. Taking it a step further, I am also interested in seeing if there is a correlation between growing trend in “Hadoop” and “Big Data”. Also, I wanted to see how it compares with the Terms like Business Intelligence and Data Science. With this, I turned to Google Trends to quickly create a Trend report to see the results.

Here’s the report:

Big Data Hadoop Business Intelligence

Here are some observations:

1) There’s a correlation between Trend of Big Data and Hadoop. In fact, it looks like growing interest in Hadoop fueled interest in “Big Data”.

2) Trend line of Big Data and Hadoop overtook that of Business Intelligence in Oct 2012 and sep 2012 respectively.

3) Decline in Trend line of Business Intelligence.

4) There seems to be a steady increase in Trend line for Business Analytics and Data Science.

And Here’s the Google Trend report URL:

What do you think about these trends?

Three V’s of Big Data with Example:


In this blog-post, we would see the Three V’s of Big Data with Example:

1. Volume:

TB’s and PB’s and ZB’s of data that gets created:

From the webinar “How to Walk The Path from BI to Data Science: An interview with Michael Driscoll, data scientist and CEO of Metamarkets” – A global surge in Data

2. Velocity:

The speed at which information flows.

Example: 50 Million tweets per day!

twitter 50 million tweets per day

(This is back in Nov. of 2010 – the number must have increased!)

UPDATE 23 Nov 2012: on, wikipedia it says – 340 million tweets per day!

twitter 2012 340 million tweets per day

3. Variety:

All types of data is now being captured which may be in structured format or not.

Example: Text from PDF’s, Emails, Social network updates, voice calls, web traffic logs, sensor data, click streams, etc

data variety big data

Image courtesy

And this may be followed by other V’s like V for Value.


In this blog-post, we saw Three V’s of Big Data with Example.

Related Posts:

Who on earth is creating “Big data”?

Examples to help clarify what’s unstructured data and what’s structured?

“An unexpected system error occured…” – While trying to establish a Data Connection in Performance Point 2010 Dashboard Designer


So I got an error while trying to set up a Data Connection via Performance Point 2010 Dashboard Designer: “An unexpected system error has occurred . additional details have been logged for your administrator” – and so I did quick searches and read this & this & this & this & this and with the help of the links I solved the error. Now, there are lots of moving parts but for machine I was able to solve the error by:

1. SharePoint 2010 Central Administration

2. Manage Services on Server

3. Stopping “PerformancePoint Service”

4. And then Starting it Again.

5. If you are still facing issues then consider re-booting the server. In my case, it was a demo machine and so I quickly rebooted it.

Simple? Yeah but I spent 30 odd mins trying to figure out how to solve this error and so I thought I would document this.


Works? Yes? Great! No? Try:

-> Configure secure service store and unattended service account.

-> you can check out the links that I added earlier.


Before I got the error – I had

1. Successfully Added “PerformancePoint Service Application” via “Manage Service Applications”

2. I had made sure that the PerformancePoint Service and the Secure Store Service were Started.

3. Created a Business Intelligence Center Site and checked the Site Collection Features were properly configured.

But I got an error while trying to create a Data Connection. And I solved it! And Now can spend time creating few reports! That’s about it for this post.

performance point 2010 sharepoint business intelligence microsoft