Visa Asks Banks to Participate in Blockchain Pilot for Transfers by Jenny Surane via @infomgmt

Visa Europe Collab, the network’s London-based innovation hub, is partnering with BTL Group to explore applications for blockchain technology in financial services.

The march of blockchain carries on.

MyStory: How I transitioned to Data Science after 6 years in Data warehousing? by Balaji SR via @analyticsvidha

Prior to getting initiated to Data Science,  I was working in data intensive Data-warehousing for more than 6 years. In 2013, I had an opportunity to work in a problem wherein we were required to build a model to predict the probability of a customer buying a product as part of transformation initiative. This has widened my horizon.

Inspiration and hints on how to progress into Data Science.

How to Become a (Type A) Data Scientist by Ajit Jaokar,via @kdnuggets

This post outlines the difference between a Type A and Type B data scientist, and prescribes a learning path on becoming a Type A.

I found this really interesting.

21 Must-Know Data Science Interview Questions and Answers via @kdnuggets

KDnuggets Editors bring you the answers to 20 Questions to Detect Fake Data Scientists, including what is regularisation, Data Scientists we admire, model validation, and more.

Something that needs to be read and made sure you have learnt. This is a three page article.

WEBINAR: How Not to Be Wrong About Visualization - 13 September 2016

Overview

Title: How Not to Be Wrong About Visualization

Date: Tuesday, September 13, 2016

Time: 09:00 AM Pacific Daylight Time

Duration: 1 hour

Summary

How Not to Be Wrong About Visualization

Many of the things we take for granted in visualisation are based on nothing other than hearsay and maybe somebody’s aesthetic judgement. Even seemingly obvious things turn out to be wrong when we start to question them.

In this DSC webinar, Robert will walk you through a number of examples that show the limits of what we know about visualisation. As a particular example, he will talk about his recent research on pie charts. Yes, pie charts! How do we read pie charts? Look at any number of books, and they will tell you that we look at the central angle of a slice. That is important, because it means that removing the enter (like in a donut chart) will lead to less accuracy. But it's not true. And worse, this question hasn't been studied since 1926 — ninety years ago! It’s only one of the most used chart types out there, and yet there are lots of things we don’t know about it.

Attend this DSC webinar and find out what else you’re probably wrong about!

Speaker: Robert Kosara, Visual Analytics Researcher -- Tableau 

Hosted by: Bill Vorhies, Editorial Director -- Data Science Central

Register here

Yuval Noah Harari on big data, Google and the end of free will via @FT

It's not just external forces that are making data-based decisions that affect our lives. In this essay, the historian Yuval Noah Harari argues that Dataism is diminishing our ability to listen to ourselves and "free will" may be slipping away.

This was incredibly interesting and really makes you think.

SLIDESHOW: 5 Steps to Maximizing the Value of Your Big Data Lake via @infomgmt

Big data lakes have created a lot of change, a lot of angst and most importantly -- a lot of opportunity, according to Avi Kalderon, big data and analytics practice leader at NewVantage Partners. Here are five ways in which you can maximise the value of your data assets.

Interesting comments.