In a prior post I outlined some thoughts on the outlook for the data analytics sector and referenced a database I prepared of analytics companies. At the time the list comprised about 400 names categorized into a number of sectors and segments.
I’ve continued to update the list since that time and it now comprises about 800 companies.
This article on going deeper into regression analysis with assumptions, plots & solutions, was posted by Manish Saraswat. Manish who works in marketing and Data Science at Analytics Vidhya believes that education can change this world. R, Data Science and Machine Learning keep him busy.
Regression analysis marks the first step in predictive modeling. No doubt, it’s fairly easy to implement. Neither it’s syntax nor its parameters create any kind of confusion. But,…Continue
Added by Emmanuelle Rieuf on September 8, 2016 at 12:00pm — No Comments
In this day and age, you can’t go a day without hearing terms such as “data science,” “big data,” or “analytics.” These terms have been thrown around to apply to so many situations that the original meaning of these words is lost.
So, what does it take for any organization to be successfully data-driven? Although analytics may seem complicated, the solution comes from simplicity.
I believe it comes down to four things, as I’ve illustrated below: business need, clean data…Continue
Return on Investment (ROI) is defined as the ratio of a return (benefit or net profit) over the investment of resources that generated this return. Both the return and the investment are typically expressed in monetary units, whereas the ROI is calculated as a percentage.
ROI formula: (Return – Investment)/Investment
It’s typically expressed as a percentage, so multiply your results by 100.…Continue
Added by Amy Porras on August 12, 2016 at 2:30am — No Comments
“Alone we can do so little and together we can do much” - a phrase from Helen Keller during 50's is a reflection of achievements and successful stories in real life scenarios from decades. Same thing applies with most of the cases from innovation with big impacts and with advanced technologies world. The machine Learning domain is also in the same race to make predictions and classification in a more accurate way using so called ensemble method and it is…Continue
Added by Valiance Solutions on August 11, 2016 at 12:00am — No Comments
Summary: To ensure quality in your data science group, make sure you’re enforcing a standard methodology. This includes not only traditional data analytic projects but also our most advanced recommenders, text, image, and language processing, deep learning, and AI projects.
A Little HistoryContinue
Can Pre-hire Talent Assessments Be a Part of a Predictive Talent Acquisition Strategy?
Over the past 30+ years, businesses have spent billions on talent assessments. Many of these are now being used to understand job candidates. Increasingly, businesses are asking how (or if) a predictive talent acquisition strategy can include the use of pre-hire…
Added by PIYASHI BHATTACHARYYA on July 21, 2016 at 5:00am — No Comments
This post highlights a number of important applications found for deep learning so far. It is well known that 80% of data is unstructured. Unstructured data is the messy stuff every quantitative analyst tries to traditionally stay away from. It can include images of accidents, text notes of loss adjusters, social media comments, claim documents and review of medical doctors etc. Unstructured data has massive potential but has never been traditionally considered as a source of insight before.…Continue
Added by Syed Danish Ali on June 26, 2016 at 5:00am — No Comments
This video was built as a result of our internal hackathon using Teradata Listener to absorb real time small messages from Transformers and other devices on the Power Grid in Southern California. The video demonstrates a real time predictive analytic showcasing proactive repairs of the power grid to reduce costs and avoid disruptions of power service.…
Added by John Thuma on June 9, 2016 at 1:00am — No Comments
For companies newly endeavoring in establishing capabilities in Data Science, it is important to keep a few crucial points in mind. Clean data, applicable models, and business intuition are all key to success. Do not remove any of them from the equation. Data Science is essentially about identifying and/or creating the cleanest possible data set, then searching mathematically for patterns within it. The goal should be to help business users make important data-driven…Continue
Added by Gaurav Agrawal on June 8, 2016 at 6:01am — No Comments
I created an R package for exploratory data analysis. You can read about it and install it here.
The package contains several tools to perform initial exploratory analysis on any input dataset. It includes custom functions for plotting the data as well as performing different kinds of analyses such as univariate, bivariate and multivariate investigation which is the first step of any…Continue
Added by Ujjwal Karn on May 18, 2016 at 8:30am — No Comments
Summary: Will Automated Predictive Analytics be a boon to professional data scientists or a dangerous diversion allowing well-meaning, motivated but amateur users try to implement predictive analytics. More on the conversation started last week about new One-Click Data-In Model-Out platforms.
I have always been very much…Continue
More and more organizations today are moving to unified communications (UC) platforms for better communications within their organization, with their customers and with their partners. These platforms combine voice, email, chat and web into a seamless Omni-channel experience for its users. They today boost of a number of features, but most of them provide either static or rule based experiences. Given that these platforms generate tons of data, can this data be used to improve user…Continue
Added by Kumaran Ponnambalam on March 30, 2016 at 4:30pm — No Comments
Regression is the first technique you’ll learn in most analytics books. It is a very useful and simple form of supervised learning used to predict a quantitative response.
Originally published on Ideatory…
Added by Sudhanshu Ahuja on March 28, 2016 at 8:00pm — No Comments
At my LinkedIn Profile, I recently got an email from a Dell Recruiter who was looking to interview me for a Marketing Data Scientist position that she was trying to fill. The location was all wrong for me, but the email really got me thinking about marketing data science, and what it was about my LinkedIn profile that had piqued her interest.
I mean, as a small business owner, I wear many hats… In fact, I’d say that about 30% of the work I do with my business is related to marketing…Continue
"Information is the oil of the 21st century, and Analytics is the combustion engine."
The Volume, Variety and Velocity of data coming into your organization continue to reach unprecedented levels. This phenomenal growth means that not only…Continue
Added by Anuj Tripathi on February 26, 2016 at 12:00am — No Comments
Whether you love it or hate it, predictive analytics has already helped elect presidents, discover new energy sources, score consumer credit, assess health risks, detect fraud and target prospective buyers.
Predictive analytics is business intelligence technology that produces a predictive…Continue
Added by Anuj Tripathi on February 18, 2016 at 12:00am — No Comments
By Greta Roberts.
It’s exciting to watch advances in predictive and prescriptive employee solutions. A public HR technology company recently announced the release of an application enabling employers to “identify which employee is likely to quit, and what options need to be considered to retain that…Continue
Added by Mike Kennedy on February 16, 2016 at 4:00am — No Comments