The big data analytics space is evolving at a tremendous speed, so is the terminology used in the space. This terminology is sometimes really hard to understand. Here is a list of […]
Big Data Glossary – Part 1
Big Data Insights: Reinventing Customer Experiences
The importance of gathering and managing the right consumer data, applying analytics to generate valuable insights and translating those insights into effective front-line action cannot be emphasized enough for companies, especially those […]
Characteristics that make Big Data – Big
The sustained success of companies that run over the Internet like Google, Facebook, Amazon, etc. provides evidence that there is a fourth factor of production in today’s hyper – connected world. Besides, […]
Big Data Analytics – Touching Life
The world is excited about big data and high precision analytics not only because the data is extensive but also because its’ potential impact is huge. Successfully capturing this potential of advanced […]
Anticipating the Changes in Big Data Analytics
Big data and analytics have immense potential in many industries from banking to sports and from medicine to retail. The effective use of data for creating business value is important, even if […]
Why you might use SAS
I write a good bit of content about using open-source tools for analytics and operations research. However, my workhorse happens to be SAS. Actually, I use SAS Enterprise Guide (EG) and SAS […]
Data Science Jargon – Why your client might not be listening
To effectively communicate, we must realize that we are all different in the way we perceive the world and use this understanding as a guide to our communication with others. —Anthony Robbins Words […]
What the heck are “Predictive Models”?
Predictive modeling (#PredictiveAnalytics) does not lie solely in the domain of Big Data Analytics or Data Science. I am sure that there are a few “data scientists” who think they invented predictive […]
Seven Analytics Lessons I’ve Learned (So You Don’t Have To)
Be prepared to Wrangle – When dealing with “big data” (#bigdata), about 2/3 of you project time is spent getting access to the data, getting the right data, preprocessing the data, and […]
A 12 Step Approach to Analytical Modeling
Define the problem – Defining the problem is necessary. Defining the “right” problem is absolutely critical, otherwise you’re just wasting everyone’s time. However, the customers you are working for may not know […]
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