Summer Readings from my Google+ Page

While blog preserving my observations and thoughts, it preventing me to spend enough time to read what other people thinking and saying, so I created almost 2 years ago the extension of this blog in the form of 2 Google+ pages and , where I accumulated all reading pointers for myself and gradually reading those materials when I have time.

Those 2 pages magically became extremely popular (this is unintended result) with total more than 5000 Google+ followers as of today. For example here is a Chart showing monthly growth of the  number of followers for the main extension of this blog :


So please see below some samples of Reading Pointers accumulated over last 3 months of summer by my Google+ pages:

Author trying to simplify BigData Definition as following: “BigData Simplified: Too much data to fit into a single server”:

Recent talk from Donald Farmer:

Dmitry pointing to implementation Disaster of Direct Discovery in Qlikview 11.2:

Specs for Tableau in Cloud:

The DB-Engines Monthly Ranking ranks database management systems according to their popularity. Turned out that only 3 DBMSes are popular: Oracle, SQL Server and MySQL:

According to Dr. Andrew Jennings, chief analytics officer at FICO and head of FICO Labs, three main skills of data scientist are the same 3 skills I tried to find when hiring programmers for my teams 5, 10, 20 and more years ago: 1. Problem-Solving Skills. 2. Communications Skills. 3. Open-Mindedness. This makes all my hires for last 20+ years Data Scientists, right? See it here:

A study finds the odds of rising to another income level are notably low in certain cities, like Atlanta and Charlotte, and much higher in New York and Boston:

Tableau is a prototyping tool:

Why More Data and Simple Algorithms Beat Complex Analytics Models:

New Census Bureau Interactive Map Shows Languages Spoken in America:

Google silently open sourced a tool called word2vec, prepackaged deep-learning software designed to understand the relationships between words with no human guidance. It actually similar to known for a decade methods called PLSI and PLSA:

“Money is not the only reward of education, yet it is surely the primary selling point used to market data science programs, and the primary motivator for students. But there’s no clear definition of data science and no clear understanding of what knowledge employers are willing to pay for, or how much they will pay, now or in the future. Already I know many competent, diligent data analysts who are unemployed or underemployed. So, I am highly skeptical that the students who will invest their time and money in data science programs will reap the rewards they have been led to expect.”:

Some good blog-posts from InterWorks:

Technique for using Tableau data blending to create a dynamic, data-driven “parameter”:

More about Colors:

Russian Postcodes are collected and partially visualized:

EXASolution claims to be up to 1000 times faster than traditional databases and the fastest database in the world – based on in memory computing.

web interest to Tableau and Qlikview:


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