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January 2014 Blog Posts (50)

Big Data books - Data Science, Analytics, and Machine Learning. Oh my!

The mantra is famous in Hollywood history: "Lions, and Tigers, and Bears. Oh my!"  It brought fear to young viewers everywhere. But, as the story goes, it was soon obvious that there was nothing to fear. 

With so much Big Data noise, and hype, and pressure (oh my!) pressing in on us from all sides, there is understandable fear and loathing around the concept of Big Data. In my opinion, the way to…


Added by Kirk Borne on January 21, 2014 at 7:58am — 1 Comment

10 Great Attributes of Jigsaw Academy's HR Analytics Certification Course

I have been reading about Jigsaw Academy's new HR Analytics Training Course, which starts soon (January 26, 2014). HR Analytics is a remarkably interesting new field -- or, one could say, an old field with exciting new dimensions! The application of…


Added by Kirk Borne on January 20, 2014 at 9:30pm — No Comments

Replaying the NFL Championships with Twitter Language Analytics

Excerpt reprinted with permission from

By CKM Advisors Natural Language Analysis Team, 

Last year we posted a popular piece offering our view on…


Added by Nicholas Hartman on January 19, 2014 at 11:43pm — 2 Comments

Choosing the appropriate Clustering Algorithm (Video)

This is a short video that contains the criteria that I use while choosing the appropriate clustering algorithm. If you have other criteria that you use, please do let me know by leaving a comment on my blog or by reaching out to me on Twitter @VRaoRao Thanks!

Added by Venky Rao on January 18, 2014 at 7:35am — No Comments

The Power of Bubble Charts

Check out this post on using Plotly bubble charts to display three or even four dimensions of data:

Below is a chart with the interactive, text on the hover experience you can get if you view the page.…


Added by Matthew Sundquist on January 17, 2014 at 9:00am — No Comments

Weekly digest - January 20

Featured Articles


Added by Vincent Granville on January 16, 2014 at 11:00am — No Comments

Data Scientist versus Business Analyst

Business analysts focus on data base design (database modeling, at a high level, including defining metrics, dashboard design, retrieving and producing executive reports and designing alarm systems), ROI assessment on various business projects and expenditures, and budget issues. Some work on marketing or finance planning and optimization, and risk management. Many work on high-level project management,…


Added by Vincent Granville on January 16, 2014 at 9:00am — 3 Comments

Data Scientist versus Data Engineer

One of the main differences between a data scientist and a data engineer has to do with ETL versus DAD:

  • ETL (Extract/Load/Transform) is for data engineers, or sometimes data architects or database administrators (DBA).…

Added by Vincent Granville on January 16, 2014 at 9:00am — 2 Comments

Data Scientist versus Data Architect

I recently had the following discussions with a number of data architects, in different communities, in particular (but not limited to) the TDWI group on LinkedIn. This is a summary of the discussion, featuring differences between data scientists and data architects, and how both can work together.



Added by Vincent Granville on January 16, 2014 at 9:00am — 2 Comments

Data Scientist versus Statistician

Many statisticians think that data science is about analyzing data, but it is more than that. Data science also involves implementing algorithms that process data automatically, to provide automated predictions and actions, such as:

  • Automated bidding systems…

Added by Vincent Granville on January 16, 2014 at 9:00am — 2 Comments

Six categories of Data Scientists

We are now at 9 categories after a few updates. Just like there are a few categories of statisticians (biostatisticians, statisticians, econometricians, operations research specialists, actuaries) or business analysts (marketing-oriented, product-oriented, finance-oriented, etc.) we have different categories of data scientists. First, many data scientists have a job title different from data scientist, mine…


Added by Vincent Granville on January 16, 2014 at 8:30am — 11 Comments

Markov Logic Networks for Better Decisions

One important goal of data science is to help decision makers make better decisions. Markov…


Added by Michael Walker on January 15, 2014 at 12:24pm — 1 Comment

Agile VS Traditional Project Management

This article outlines the differences between Agile and Traditional Project Management. APM vs TPM, where APM stands for Agile Project Management and TPM stands for Traditional Project Management. APM focuses on customer interaction and satisfaction, where as TPM focuses on artifacts and Plans and adherence to the Plan. APM responds to and change by using adaptive actions, where as TPM adheres to Change Management and tight control by using corrective actions. 

APM deals with…


Added by Atif Farid Mohammad on January 14, 2014 at 11:55am — No Comments

In-place Computing Model: for Big and Complex Data

As we've seen how in-place and in-memory work differently, today we are sharing more fundamentals of in-place computing model. This models was designed to solve "Big and Complex Data," - not just about size but more about the complexity. We see many analytic cases today incorporate…


Added by Yuanjen Chen on January 13, 2014 at 12:30am — 2 Comments

The Data Triangle: A Simple Framework For Data

In my latest video blog, I provide an overview of a simple framework that I developed to discuss data.  You can view it here:

Added by Venky Rao on January 11, 2014 at 7:21am — No Comments

10 ways for Banks to achieve greater profit and customer satisfaction

While Banks are getting more and more pressure from customer’s increasing demand, highly competitive market and strict regulations – in the current environment, understanding customer behavior, attitudes and requirements is more vital than ever for banks’ strategic thinking, operational planning and day-to-day customer treatment, according to Ernst & Young.



What Banks can do?


  1. Product Bundling and Relationship Pricing – Banks…

Added by Mousumi Ghosh on January 9, 2014 at 1:01pm — No Comments

Data Science – the Foundation for Leading Banks


Now-a-days, Banking Industry is facing many challenges - rapidly changing consumer environment, rigorous regulatory guidelines, highly competitive environment, emergence of new channels to name a few.


With these great challenges come great…


Added by Mousumi Ghosh on January 9, 2014 at 12:56pm — No Comments

Weekly digest - January 13

Featured Articles


Added by Vincent Granville on January 8, 2014 at 11:00am — No Comments

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