Added by Vincent Granville on June 12, 2013 at 12:00pm — No Comments
I have two databases on Microsoft SQL Server (daily business activities performed) and also on peachtree and on orange human resources software. I want to build a data warehouse with this databases available. My questions are:
i. Where can I integrate all these databases together
ii. After I integrate, how can I mine this data?
iii. What is the best software to use and mine this data?
iv. Can combining all these databases produce insight…Continue
Added by Adetula Oluwabunmi on June 12, 2013 at 4:51am — No Comments
There's a lot of talk these days about how governments use all the data they can put their hands on, to monitor every individual in the world. Capabilities offered by big data storage and analytic processing are immense, when in the hands of professional, capable data scientists. Last week the National Security Agency was under the spotlight, a month ago it was the IRS (Income Revenue Service) for a biased auditing …Continue
Nowadays we hear a lot about big data, cloud, or the big data analytics on cloud. One of the underlying needs here is the data storage. It is stored as 0’s and 1’s in some datacenters. It isn’t cheap to maintain all of this data. Looking at the heat generated by these datacenters, it isn’t even environment friendly.
Can this data be really in the clouds? (The real clouds formed in the sky) :)
In India we have heard about Rishi’s who used to sit under a tree and meditate for…Continue
Added by Shinto Paul on June 11, 2013 at 8:30pm — No Comments
Guest post by Emily Bailey, Nathan Srinivas, and Barry Fischer. First published June 6, 2013, in Opower.
Over the past couple of years,…Continue
There are two major perspectives of Data Science we can look at:
- Consumer/User Perspective
- Data Scientist’s Perspective
This article explores these two areas to ponder upon in little more depth.
- Consumer/User Perspective (User will not like “noise”)
A single user/consumer might need some analysis to either start some study or make some decisions. This single user might be a CIO/CTO or perhaps we can also say that this single user is a group of decision…Continue
Added by Atif Farid Mohammad on June 11, 2013 at 10:40am — No Comments
Your data is like Gruyere. It has holes. Big holes, sometimes the empty space occupies a bigger volume than the data itself - just like dark matter is more abundant than visible matter in the universe. This article is not about shallow or sparse data, but instead about data that you do not see, that you do not know even exist, and yet, data that contains better actionable nuggets than anything in your…Continue
Indirectly of course. There are other factors too, such as regulations which make it illegal to sell un-pasteurized milk, horse meat, foie gras, etc., but the biggest factor influencing what the average American eats is the margin the grocery store makes on the products it sells. This explains why you can't get redcurrants or passion fruits anymore, but you'll find plenty of high energy drinks and food rich in sugar…Continue
The easiest person in the world to fool is yourself. Data scientists sometimes fool themselves - in matters trivial and important. Thus, I strongly suggest that we acknowledge real or subconscious biases in ourselves, the data, the analysis and group think. It is prudent for data science teams to have…Continue
Added by Michael Walker on June 6, 2013 at 12:11pm — No Comments
Bob Muenchen's very useful work on this topic, SAS Dominates Analytics Job Market; R up 42% sent me back to some 2012 work we did at Statistics.com on the subject of what employers are looking for in the way of analytics skills. First, our main results:
1. Our numbers showed a much less SAS-dominant world: 1.92 SAS jobs for every R job. Bob had found the ratio to…Continue
Recently named by Business Insider as one of the Big Data startups to watch, Alpine Data Labs is experiencing massive growth and is currently on a hiring spree, looking for top talent. Alpine is hiring solution architects, software engineers, data scientists, marketing & sales pros, and technical support engineers. Send your resume and a note to [email protected]…Continue
We have tried to synthesize the most disruptive big data use cases into a compact . 3 Minute video
It covers 6 use cases , 4 healthcare data streams and hopefully sets the stage for curating more use cases in an area which truly needs a lot of healthy transformations !!!
Added by derick.jose on June 5, 2013 at 10:20am — No Comments
I looked at the job titles of my 7,500 LinkedIn connections, and found about 4,900 unique job titles. The vast majority of my connections work in data science or some analytic field. Some very popular job titles do not contain an analytic keyword: for instance CEO, Consultant, Founder. My own job titles - Co-Founder, Managing Partner - fall in this category despite the fact that among other things and foremost, I am…Continue
“Golf is deceptively simple and endlessly complicated”
Yvonne Buysman, Sports & Fitness Fellow for The (ART+DATA) Institute helps us understand how the data helps design a better round of golf. Her writing reveals the effect of an instant feedback loop in golf .…Continue
Added by Zach Piester on May 31, 2013 at 4:18am — No Comments
As data science evolves into a separate and distinct scientific and business discipline, there is talk about the death of traditional statistics. It is true that today's large data sets are unlike the ones we analyzed in graduate statistics classes. It is also true that big data…Continue
Below is information found today on Kaggle. This flat rate applies regardless of the consultant's age - but only the "best" data scientists are allowed to work on business projects posted by campanies like us (we are going to submit a very interesting project next week). Yet, not sure how much the data scientists are…Continue
During analysis of movements of individuals in public places, there are only two dimensions that can represent movement of an individual, shown via data saved between starting and end point, even incorporating elevators and stairs to different (shop) levels). That is a multi-linear way of looking at movements of individuals in crowds in a specific environment. Most big shopping corporates use these kinds of analysis methods.
But what if (like in 3D environments) movement can be up and…Continue
Added by Emmanuel P. Gruijs on May 24, 2013 at 3:14am — No Comments