Added by William Vorhies on October 8, 2015 at 7:26am — No Comments
In an era of information, the use of Big Data analytics in the banking and financial services in India can be traced back to the early 2000s and the bank with the most actionable insights is the winner. While, more than 70% of the banking executives worldwide say customer centricity is important to them, this requires a deeper…Continue
Added by Aureus Analyitcs on October 7, 2015 at 11:04pm — No Comments
The weekly digest now has 6 sections: (1) Featured Articles and Case Studies, (2) Featured Resources and Technical Contributions, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content.
The full version is always published Monday. Starred articles are new additions or updated content, posted between Thursday and Sunday.…Continue
Added by Vincent Granville on October 7, 2015 at 6:30pm — No Comments
More than 50 years after the term "data science" was coined, there continues to be a debate about its precise definition and what a career in data science entails.
This debate too often consists of opinions, personal and professional biases, and anecdotal evidence. Surprisingly, very rarely is it…Continue
Added by Yevgeniy Slutskiy Meyer on October 7, 2015 at 10:58am — No Comments
Added by Martin Doyle on October 7, 2015 at 5:43am — No Comments
Added by Damian Mingle on October 6, 2015 at 3:27am — No Comments
More and more people are becoming aware of the need to conserve water for environmental reasons. Due to restrictions surrounding drought-related water use, the water utilities are finding themselves struggling due to less sale of water to the customers and hence facing challenges to stay financially sound. Water is increasingly becoming one of the world’s most precious resources, and hence data scientists are working continuously to help water companies and…Continue
Added by Sameer Dhanrajani on October 6, 2015 at 2:30am — No Comments
With the advent of technology, data is being generated at a fast pace. In order to handle this humongous quantity of data, one needs technologically improved tools which can help to analyze this huge amount of data. These tools help in giving meaning to the information which can be used to strategize organizations future steps. It helps to understand the hidden patterns…Continue
Added by Aureus Analyitcs on October 5, 2015 at 10:00pm — No Comments
Summary: Over 80% of companies are not yet using advanced analytics. Here’s a step-by-step plan to implement a brand new predictive analytics program getting the biggest bang for your buck from the most cost effective investment.
Are You (Your Company) Part of the 80% or the 20%?…Continue
Added by William Vorhies on October 5, 2015 at 3:00pm — No Comments
We have published many articles on this subject, for instance:Continue
The year was 2006. LinkedIn had done the improbable. People started to notice them. They had momentum on their side edging towards 10 million users. There was one problem. The holy grail of networking is connecting with other folks and expanding networks. People were inviting other people but not connecting with people already there on LinkedIn.
A LinkedIn employee, Jonathan loved playing with data. He did…Continue
Added by Sudhanshu Ahuja on October 5, 2015 at 7:00am — No Comments
Financial Modeling training courses are all around the web and there has been lot written about learning Financial Modeling, however, most of the financial modeling courses are exactly the same. This goes beyond the usual gibberish and explore practical Financial Modeling as used by Investment Bankers and Research Analysts.
In this Free Online Financial Modeling Training Course, I will…Continue
Added by rajesh dhnashire on October 4, 2015 at 7:58pm — No Comments
Opportunities for talented data scientists – both seasoned professionals and enthusiastic newcomers -are everywhere. Long gone are the days when a desire to work with statistics, analytics or predictive modelling would restrict you to the IT or financial sectors when searching for work. Recently I’ve written about innovative data strategies being undertaken by companies in…Continue
Added by Bernard Marr on October 4, 2015 at 5:30pm — No Comments
Time Series IoT applications in Railroads
Authors: Vinay Mehendiratta, PhD, Director of Research and Analytics at Eka Software
and Ajit Jaokar, Data Science for IoT course
This blog post is part of a series of blogs exploring Time Series data and IoT.
The content and approach are part of the Data Science for Internet of…Continue
Added by ajit jaokar on October 4, 2015 at 12:18pm — No Comments
When discussing the use of algorithms, the issue of durability or portability has to be considered. For example, a stock trading algorithm might be used in a missile guidance system. The algorithm would have to operate on an abstract kinetic level rather than for a specific application. I have written in the past about using the same algorithm to study stocks, earthquakes, hurricanes, electro-cardiograms, and attempts at evasion - using my mouse in a game environment. Wouldn't an abstraction…Continue
Added by Don Philip Faithful on October 4, 2015 at 7:17am — No Comments
I spent way too much time sorting through all the information collected on Data Science. All I knew in the beginning is that it had something to do with math and statistics and algorithms (which are love), and computers (which are hate not so much love). It's finally starting to fall into place. I made a preliminary list of all the things I should learn. In the process, I stumbled upon Clare Corthell's "Open Source Data Science Master's…Continue
Added by Elma Bratovic on October 3, 2015 at 9:37pm — No Comments
Cluster Analysis is a common technique to group a set of objects in the way that the objects in the same group share certain attributes. It’s commonly used in marketing and sales planning to define market segmentations.
Added by Yuanjen Chen on October 2, 2015 at 1:21pm — No Comments
Added by Michael Walker on October 1, 2015 at 8:07pm — No Comments
The Data Science Association (DSA) and Google is interested in learning more about your experience with tools and training. Click on the link below to take a 10-minute survey for data scientists.…Continue
Added by Michael Walker on October 1, 2015 at 7:53pm — No Comments
Econometrics is fundamental to many of the problems that data scientists care about, and it requires many skills. There's philosophical skill, for thinking about whether fixed effects or random effects models are more appropriate, for example, or what the direction of causality in a particular problem is. There's some coding, including knowing the right commands to interact with statistical programs like Stata or R, and how to interpret their output. There's the intuition to know which…Continue