The full version is always published Monday. Starred articles or sections are new additions or updated content, posted between Thursday and Sunday. 

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• Popular Software Skills in Data Science Job postings *…

While large data sets may provide significant value in certain cases, data diversity and integrating smart data points will provide more consistent actionable insights and high value intelligence leading to better decision-making.



For example, consider NFL football data. Focusing on large football game data sets is usually not helpful and often misleading creating…

Obviously, there are few topics that are as morbid as our own morbidity, and it is for this reason that we often avoid thinking about it. However, as it turns out, how we view the probability of the causes and the timing of our own demise is very important. Why? It is because these views are subconsciously affecting how we approach health related decisions that we are making every day.

Think of it this way. If you believed that you would likely die from an…

A couple of weeks ago, my team was asked to come up with a solution for an Enterprise Complaints Platform with Advanced Analytics capability for a Fortune 50 Bank. The initial scope statements were high level requirements like for example, Identification of high risk complaints that were likely to be escalated to regulatory agencies, Complaint Root Cause Analysis, etc.

It quickly became apparent that while the solution did include Advanced Analytics components what was really needed…

As data scientists, we get excited about using our talents to solve problems like global climate change and worldwide environmental policy.

This week, I have the opportunity to represent Pivotal and team with other experts from EMC, Earthwatch, and Schoodic Institute to spend a week at…

Three thoughts this time, for our first edition of Thoughts of the Week.

Thought #1

An estimate that is slightly biased but robust, model-independent, easy to compute, and easy to interpret, is better than one that is a non-biased, difficult to compute, mysterious, or not robust. That's one of the differences between data science and statistics.

Thought #2

Learning how to code, especially SQL, should be the last step in…

Introduction

I've been writing a Tableau and Alteryx-focused blog for 1.5 years on Wordpress and haven't thought of writing anything here on DSC. I just completed a two-part series that discusses solving problems using innovative approaches with Alteryx and Tableau, which were my 99th and 100th blog posts. They are longer than usual but offer a good insight into my background and why I write a technical blog.

My blog is focused…

They say that breaking up is hard to do. Now, data scientists know that it’s true. Neil Sedaka songs aside, they know it’s true because, in 2013, with the help of public data sourced from Twitter, they were able to track and listen-in on conversations between 661 couples who were in the process of ending their relationships.

Researchers Venkata…

The case study presented here - including root cause analysis and solution - was performed for a digital publisher. It offers a different perspective on what data scientists are capable of. The expert involved here is not a coder, certainly not a production guy, yet is able to leverage his business acumen and domain expertise to

• Imagine dozens of scenarios and rank them by chance of occurring
• Get silo-ed data from various departments (finance, sales, marketing, product,…

The end goal of pervasive analytics is simple and will change the way in which the world operates today. By feeding individuals the right information, at the right time, analytics become invisible and embedded into every application and workflow of every user. It is a vision, a goal, a strategy that every individual across every industry can rally around in order to drive the business metrics that matter…

The "big data" and/or "analytics" buzz have been around for a while now and have clearly made a major impact on many things. However, in HR, I'm not entirely sure what kind of impact it has made. On some level, I think the big data buzz, at least, pushed HR to be more strategic and to think more strategically. With the increased emphasis on data brought on by the big data movement, it led many, including HR to be analytical and to use data and evidence to make informed decisions and develop…

We read articles about problems in companies due to customer experience and we wonder why with all the hype about data and analytics these companies are blind to the facts. In todays business environment the term customer experience is frequently followed by the word data.

“We monitor our customer experience using massive…

Skills, skills, skills!!! Which ones should I learn? Which ones do I need to land the job, to impress the client, to prepare for the future, to stay relevant? What programming languages should I learn? What technologies should I master? What business books should I read? Is there a course I can take, or a certification I can enroll in? Should I focus on being a…

This is the second article in a series. The first article is available here.

How to implement a temporal database

Not every database requires a temporal database implementation, but some do. We can help you get started. As discussed in our previous article, the SQL-2011 standard included clauses for the definition of temporal tables as…

The full version is always published Monday. Starred articles or sections are new additions or updated content, posted between Thursday and Sunday. 

Featured

• The Only Skill you Should be Concerned With * …

Based on requests from clients - vendors of data processing platforms and products - as well as trends in popular blogs,  job postings, and my own reading. Here are a few topics recently gaining strong traction (items beyond #13 were recently added)::

1. The rise of data plumbing, to make big data run smoothly, safely, reliably, and fast through all "data…

Summary:  Thanks to the IOT (internet of things) an internet-like experience of recommendations and awareness of your preferences is coming to the brick and mortar store near you.

You’ve probably noticed the huge difference in the tone of the conversation between data scientists and the general public over the issue of privacy and…

In this article, I share some of my unusual views about big data and data science. My next article will be about new trends in data science.

Big data is necessary in more applications than people think

And used with success. It includes

• Scoring transactions (credit card purchases) in real time
• Automated piloting
• Monitoring car traffic (sending alerts, finding optimum routes). Same with planes.
• Digital…