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All Blog Posts (8,067)

A Step-by-Step Plan for Getting Your Company Started with Predictive Analytics – Part 1

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%?…

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Added by William Vorhies on October 5, 2015 at 3:00pm — 1 Comment

Data Scientists: Skills Mix, Team Makeup

We have published many articles on this subject, for instance:

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Added by L.V. on October 5, 2015 at 11:30am — 1 Comment

Can You Make Data Sing? Here Are Two Big Data Analytics Success Stories. Crack this Challenge.

First one, Data Analytics leads the way to the bank

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…

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Added by Sudhanshu Ahuja on October 5, 2015 at 7:00am — No Comments

Six Companies with Great Job Opportunities for Data Scientists

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…

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Added by Bernard Marr on October 4, 2015 at 5:30pm — No Comments

Time Series IoT applications in Railroads

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…

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Added by ajit jaokar on October 4, 2015 at 12:18pm — No Comments

Inferential Modeling and Application of Analogs

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…

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Added by Don Philip Faithful on October 4, 2015 at 7:17am — No Comments

So it begins.

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…

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Added by Elma Bratovic on October 3, 2015 at 9:37pm — No Comments

Who are alike? Use BigObject feature vector to find similarities

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.



Here at BigObject we adopt a simple approach to exploring the similarities between…

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Added by Yuanjen Chen on October 2, 2015 at 1:21pm — No Comments

Data Scientists Must Focus on Data Security Risk - Cyber Risk Report 2015

Last week we discussed the importance of data scientists prioritizing client confidentiality and the concern of exposing high-value information to…

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Added by Michael Walker on October 1, 2015 at 8:07pm — No Comments

Ten (10) Minute Data Scientist Online Survey

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.…

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Added by Michael Walker on October 1, 2015 at 7:53pm — No Comments

Linear Algebra Formulas for Econometrics

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…

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Added by Bradford Tuckfield on October 1, 2015 at 2:30pm — 1 Comment

All you need to know about Hadoop

Source: http://www.edureka.co/blog/hadoop-tutorial/

Named after a kid’s toy elephant and initially recognized as a technical problem, today it drives a market that’s expected to be worth $50 billion by 2020. It is the most talked about technology since its inception as it allows some of the world’s largest companies to store and process data sets on clusters of commodity hardware.…

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Added by Durgesh Kaushik on October 1, 2015 at 9:00am — No Comments

Feature Engineering Tips for Data Scientists and Business Analysts

Most data scientists and statisticians agree that predictive modeling is both art and  science yet, relatively little to no  air time is given to describing the art. This post describes one piece of the art of modeling called feature engineering which expands the number of variables you have to build a model.  I offer  six ways to implement feature engineering and provide…

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Added by Patti Tillotson on October 1, 2015 at 5:42am — 2 Comments

Game Of Thrones - The Customer Trap and CDM (Channel Data Management)

"In that darkness the White Walkers came for the first time. They swept through cities and kingdoms, riding their dead horses, hunting with their packs of pale spiders big as hounds." - Old Nan

Like millions of other people, last night’s sleep was a little harder to come by after watching the latest episode of "Game Of Thrones". The final 20 minutes of the episode entitled…

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Added by Shubhi Gupta on October 1, 2015 at 1:00am — No Comments

Weekly Digest, October 5

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.…

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Added by Vincent Granville on September 30, 2015 at 10:30am — No Comments

Data Scientist versus Decision Scientist - Is There a Difference

Are you a data scientist or a decision scientist?  Interesting question recently raised by Deepinder Dhingra, head of products and strategy at Mu Sigma in his article ‘Data science’ misses half the equation: an argument for ‘decision…

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Added by William Vorhies on September 30, 2015 at 8:14am — 6 Comments

Big Data Insights: Reinventing Customer Experiences

The importance of gathering and managing the right consumer data, applying analytics to generate valuable insights and translating those insights into effective front-line action cannot be emphasized enough for companies, especially those that are directly consumer-facing.

Every day, retailers and FMCG companies have access to vast amounts of data, capturing information on every transaction at every store.…

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Added by Aureus Analytics on September 30, 2015 at 3:01am — No Comments

Predictive Analytics for Beginners – part 1

The role of predictive analytics in business

                                             

Data is everywhere. We generate data when using an ATM, browsing the Internet, calling our friends, buying shoes in our favourite e-shop or posting on Facebook. Companies collect this data en masse in order to make more informed business decisions, such as:

 

  • Which customers should participate in our promotional campaign…
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Added by Algolytics on September 30, 2015 at 1:34am — 2 Comments

Two great visualizations about data science

The first one is about the difference between Data Science, Data Analysis, Big Data, Data Analytics, and Data Mining:

The source for this one is, according to a tweet, onthe.io. I could not find the article in question, though this website is very interesting, but anyway, I love the above picture,…

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Added by L.V. on September 29, 2015 at 4:30pm — 4 Comments

The $1 Million Big Data Ready Challenge

Are you trying to overcome the challenges of taking your big data projects from pilot to production? Do you want to harness big data to increase customer loyalty, reduce fraud, and improve operational efficiency? Or are you using big data to solve some of the biggest challenges in your industry, whether that’s healthcare, financial services, insurance, retail, manufacturing, media and entertainment, or government services? Then Informatica can help. We are already working with customers…

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Added by Vincent Granville on September 29, 2015 at 4:29pm — 1 Comment

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