How conditionally formatting your data in Excel can help you save time in answering business questions?

Visual analytics is amazing – it helps “data enthusiasts” save time in answering questions using Data. Let’s see one such example. For the purpose of the blog post, I am going to show how to do it in Excel 2010:

Problem:

Here’s the Business Question: What was sales of Tea in North Region in 2012 Q1

Here’s the data:

SALES DATA(2012 Q1)  East West Central North South
Coffee  $  7,348.00  $  7,238.00  $  1,543.00  $  9,837.00  $    1,823.00
Tea  $  9,572.00  $  8,235.00  $  3,057.00  $  8,934.00  $  13,814.00
Herbal Tea  $  5,782.00  $  8,941.00  $  9,235.00  $     392.00  $    1,268.00
Espresso  $  9,012.00  $  2,590.00  $  4,289.00  $  7,848.00  $       340.00

So it’s easy to give out answer using the data: $8934

But let me CHANGE the business question:

WHICH Products in WHAT regions are doing the best?

Now this questions is not as easy as the previous one? WHY? because you’ll have to manually go through each number in a linear fashion to answer the question. Now imagine a bigger data-set. It’ll take even more time.

Solution

What can Excel Power users and Data Enthusiasts do to answer the new business question in an efficient way? Well, let’s see what conditional formatting can do it:

Excel Visual Analytics Conditional formatting

Now with the Data Bars, it’s easier to just glance at the report and see best performing products and regions. For instance, it’s very easy to spot that Tea is performing best in South among all products and region.

So how do you create data bars?

1. Select the data

2. Home > Conditional Formatting > Data Bars

Excel Visual Analytics Conditional formatting 2

3.Done! you’ll see this:

Excel Visual Analytics Conditional formatting

4. You can play with other options here to see what suits the best for your needs. But I just wanted to point out that there is a way for you to highlight the data in a way that helps you save time in answering business questions using data

Conclusion:

Visual analytics is a great way to quickly analyze data. In most cases, Human brain is much faster at interpreting the visual results as oppose to text/numbers – so why not use it to your advantage. And tools like Excel have inbuilt functionality to help you do that!

Business Analytics project is like an iceberg:

Business persons may not realize that Business Analytics project may involve significant efforts for the under the hood technical tasks like Data Cleaning, Data Integration, Building-a-data-warehouse, creating ETL processes, gathering business requirements among other tasks. And that explains the title of this blog: Business Analytics project is like an iceberg. It’s because, a business person may just see the tool used to visualize data but may not realize the work that went into making it “analytics-ready”. From a project management standpoint – before a project is initiated, the discussion about this different aspects of the project need to communicated to the business stakeholders so that they are in the know of efforts involved in building an analytics solution. And with that, Here’s the summary of this discussion in form of an Image:

iceberg business analytics data cleaning business intelligence data warehouse

Related articles

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: https://twitter.com/SQLGal/status/322342662013321216

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:

GEO FLOW For EXcel

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

Conclusion:

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.

Conclusion:

Data Reporting ≠ Data Analysis

Business Analytics Continuum:

Think of “continuum” as something you start and you never stop improving upon. In my mind, Business Analytics Continuum is continuous investment of resources to take business analytics capabilities to next level. So what are these levels? Douglas McDowell explained about this concept in recent post here – I think it was a great food for thought for me and hence I posting about this particular concept here. 

Here is the visual representation of the concept:

business analytics continuum

And I would encourage you to read the entire post and other posts in the series here: PASS BAC Preview Series: Business Analytics Defined

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: http://passbaconference.com/Sessions/SneakPeeks.aspx

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:

Nominal Simply names or call them set of characters Example: Full name, fruits, cars, etc
Ordinal Nominal + They have order Example: Small, medium, big
Interval Ordinal + the intervals between each value are equally split Example: 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

Ratio Interval + multiplication makes sense Weight: 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.

Thanks:

http://www.dbms2.com/2010/04/08/machine-generated-data-example/

http://en.wikipedia.org/wiki/Machine-generated_data

http://tdwi.org/articles/2012/10/23/machine-generated-big-data.aspx

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 http://bit.ly/TQAPsW

Check out some nice getting started tutorials at beyondrelational site: http://bit.ly/RVVHRV

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

— via Paras Doshi – Blog http://on.fb.me/WAQ5ky

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 http://on.fb.me/WAQ5ky

Nice collection of about 20+ videos around the topic of “Data Science”: http://bit.ly/WMkZqc

Nice collection of videos by Berkeley school of information: http://bit.ly/Tf1yAD #Information #Data

Just found Facebook’s data team’s page: http://on.fb.me/ToYILO

via V Talk Tech – A Parth Acharya Blog – Nice HeatMap of stocks! http://on.fb.me/SfBbvF

what’s the biggest fear about cloud computing? via Windows Azure http://on.fb.me/VjIiHR

Resource: Presentations from the Sentiment Analysis Symposium http://bit.ly/VtPH3B

If I switched to the newest “holiday” theme on WordPress, this is how it would look: http://on.fb.me/UEuyFr

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: http://bit.ly/VEAnkZ

Interesting tool from Google to optimize and analyze web page speeds: http://bit.ly/HTubNC

Performed #sentiment #Analysis on #starbucks twitter data using #R ! It was fun! http://on.fb.me/Z3qLo8

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. http://bit.ly/TPT9r3

Reading: Business Analytics vs Business Intelligence? http://bit.ly/YUtJwx

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? http://www.deloitte.com/view/en_US/us/Services/additional-services/deloitte-analytics-service/217c19e69249b310VgnVCM2000003356f70aRCRD.htm

For business analytics professionals: 12 webcasts on Jan 30th 2013 http://bit.ly/RUFsZ3 #sqlpass #analytics #24hop

Some nice insights about how to build an Internet platform, from the founder of Zipcar: http://bit.ly/Yco6IP

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

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