I am currently doing my PhD at UTS in Information Systems.
Please go to www.datamilk.com/survey to participate in a short simulation which tests your attitude towards a market in which individuals are financially compensated for granting access to the valuable personal data they generate as they go about their daily…
Added by rwfarrelly on August 19, 2015 at 9:30pm — No Comments
The full version is always published Monday. Starred articles are new additions or updated content, posted between Thursday and Sunday. The picture of the week is from the contribution marked with a +, where you will find the details.
Data are good for many reasons, and there are times when data are not useful. However, the good reasons outweigh the bad.
The best benefit of data is the opportunity to learn from it. When companies create atmopheres for learning, data become an asset and a strategic priority.
Another benefit of data is the opportunity to get work done quickly. However, the time needed to finish a task with the aid of data is dependent on a solid understanding of the question posed by the…Continue
Added by Salil Sheth on August 19, 2015 at 4:40am — No Comments
Added by fodop on August 18, 2015 at 9:54pm — No Comments
Analytics are like a mosquito in a nudist colony. Why? Because there are so many…Continue
Added by William Vorhies on August 18, 2015 at 10:00am — No Comments
After data science, which I discussed in an earlier post, data visualization is one of the most common buzzwords thrown around in the tech and business communities. To demonstrate how one can actually visualize data, I want to use one of the hottest tools in the market right now: Tableau. You can download Tableau Public for free …Continue
Added by Divya Parmar on August 18, 2015 at 8:25am — No Comments
It is with heavy heart that I must relay…Continue
When I think of Big Data and NoSQL I think of Big-Web-User companies like Amazon, Google, Twitter, Netflix, and other similar companies that amaze and entertain us by using the latest in NoSQL-based data science to bring us features that are useful and novel. Mostly that means using recommenders, NLP, IoT, and advanced search algorithms to present just the right part of the their Big Data databases to us users.
There aren't many examples of more traditional companies, even…Continue
Hello and Welcome back!
This series is my attempt to start cataloging all the interesting articles, industry reports, whitepapers, and news that I read every month, related to technology and data science. We are at Month 2 and let us dig right in -
This essay titled "…Continue
Added by Srividya Kannan Ramachandran on August 17, 2015 at 5:30am — No Comments
Writing SQL-MR and SQL-GR statements is made much easier by a tool I wrote while on vacation. As an Aster Data Scientist I needed a tool that would enable me to focus on the 'WHAT' and not the 'HOW!' I needed a tool to write the code for me. So I wrote Aster Tango.
Added by John Thuma on August 17, 2015 at 4:12am — No Comments
Where do you all come from?
Where do you all come from?
All your integrity's gone
Now tell me, where do you all come from?
From 'Where Do You All Come From' by Mott the Hoople
If you enjoy this piece or find it useful then please consider…Continue
Elite level athletes have long had the ability to integrate data analysis principles into their training – monitoring and crunching data on their performance to help them break personal bests and world records.
Thanks to the explosion of the Internet of Things – the idea that just about any everyday object can be made “smart”, and able to collect data and communicate wirelessly – these sort of insights are now…Continue
Added by Bernard Marr on August 15, 2015 at 7:30am — No Comments
Many CMOs have already heard of marketing attribution. Some of the good ones have already started using some level of it.
Put simply, marketing attribution refers to the practice of associating touchpoints to a conversion. The way many of us have been adamantly tracking our referrers can be called “last click attribution.” We usually determine the source from which visitors entered our page. But, we all understand that this “source” is not the only touchpoint along the…Continue
Added by Ryan Gerardi on August 14, 2015 at 9:30am — No Comments
Now that everyone is thinking about IoT and the phenomenal amount of data that will stream past us and presumably need to be stored we need to break out a vocabulary well beyond our comfort zone of mere terabytes (about the size of a good hard drive on your desk).
In this article Beyond Just “Big” Data author Paul McFedries argues…Continue
Google's BigData Library project of over 30 million scanned documents contains newly easily discovererable text searchable information, in previously neglected books and articles.
Using the ID research method (read the free sample chapter 2 of my book Nullius in Verba to find out how its done) I found numerous publications, which uniquely 100 per cent disprove the…Continue
Added by Dr Mike Sutton on August 14, 2015 at 7:00am — No Comments
Guest blog by Justin Tenuto
One of the big reasons we created our Data for Everyone initiative is that there simply aren't a ton of great open datasets out there for small businesses, startups, and academics to do work on. Sure, there are plenty of small, toy-sized datasets but those simply aren't big enough to create algorithms that anyone can trust. In fact, our founder Lukas wrote as much in this post:
Imagine if Donald Trump (or some blowhard like him, ex the misogyny) were ranting to apprentices about the current state of data analytics in “real world” corporate America.
Below are 3 Myths, Realities and Truths he might say (if he knew what he was talking about), as counterpoints to some of the (known/acknowledged) hype:
MYTH #1: Data analytics is transforming…Continue
We live in a data driven world in which we are generating, storing and analyzing more information than ever before, and at an ever-increasing speed.
Traditional “relational” databases – which store information in neat hierarchies of rows and columns aren’t suited for the big, messy datasets harvested from video, audio and even social media data streams that are needed for today’s Big Data projects.…Continue