“Predictive analytics” is a commonly used term today. Wikipedia describes it as ‘encompassing a variety of statistical techniques from modeling, machine learning, and data mining that analyze current and historical…Continue
Added by Aureus Analytics on November 21, 2015 at 12:30am — No Comments
Added by Damian Mingle on October 28, 2015 at 7:01am — No Comments
Each organizations these days is after collecting data about its customers. But very few use this data to optimum use.
Most of the organizations are clueless about the huge chunk of data that is available with them. Many companies expect the data to answer their questions. But they forget that data doesn't answer on its own. It is the analytics which help the companies give meaning to the data and provide solutions to the queries. So it is important to know the questions one has to…Continue
Added by Aureus Analytics on October 16, 2015 at 10:30pm — No Comments
Business goals are no doubt important, but in an analytic project it makes sense to balance the organization's goals with…Continue
Added by Damian Mingle on October 13, 2015 at 5:59pm — No Comments
Added by Damian Mingle on October 6, 2015 at 3:27am — No Comments
While doing a daily reading exercise about the innovations in the field of big data, I came across this interesting case study.
One of the world’s largest companies which provide refrigerated trucks wanted to increase their operational efficiency along with productivity. With this set objective they collaborated with a risk management application. The results were amazing. There was a reduction in the number of accidents by 15%. On further reading, I came across even…
Added by Aureus Analytics on September 24, 2015 at 11:31pm — No Comments
It wasn’t so long ago that the universe of data analytics companies was much easier to describe. In the year 2000 there were some clearly defined categories of companies that were all engaged in some part of the data and analytics world, although data analytics was not really recognized as a discrete sector at the time. Companies typically fit into a specific industry category, such as software (Oracle, Siebel, Epiphany), consulting (Accenture, Bain), data (credit bureaus, IMS, IRI); or a…Continue
Added by Gregory Thompson on September 21, 2015 at 7:35am — No Comments
I set out a structure for the data analytics industry in a previous post. This framework attempted to define a framework by which companies can be categorized and evaluated. The framework defined a group of four sectors with a number of segments within each of those sectors. On the one hand there is a group of global leaders that provide a comprehensive suite of analytics software and services to all-comers as well as a group of companies that have deep expertise and offerings focused on…Continue
Over the past several years, companies have moved from simply asking where to get the data from to support their decisions, to asking how they are going to leverage it to create actionable insights.
Predictive analytics use statistical or machine-learning techniques to analyze current and historical facts, and find relationships and patterns that can be used to predict…Continue
Added by Sam Button on July 13, 2015 at 6:09am — No Comments
Added by Michael Walker on June 1, 2015 at 7:30am — No Comments
What on earth makes the world go round?
Well, your guess is not far from the truth! Gone are the days when big machines were the gizmo for nerds and geeks! Today, there is a revolutionary paradigm shift in favor of small machines with capacity for big data!
Businesses are going online at a rate never imagined before in the entire history of the…Continue
Added by Christopher Alvin Mokaya on April 15, 2015 at 10:00pm — No Comments
The objective of my final project at Metis from weeks 9 to 12, is to categorize drivers based on their behaviour on the roads - their driving style and the type of roads that they follow.
The challenge associated with this objective is to identify uniquely a driver (and hence his proper “driving…Continue
Human resources analytics can provide businesses the keys to improving processes, reducing workforce costs and making the right policy changes to improve efficiency. Leaders in the space and speakers from the upcoming…Continue
Added by Alesia on January 20, 2015 at 12:00pm — No Comments
According to Deloitte’s 2014 Human Capital Trends survey, 86% of companies do not have any analytics capabilities in HR, and 67% are ‘weak’ at using HR data to predict workforce performance and improvement.
At the Workforce and HR Analytics Summit West 2015 (March 9-10, San Diego) experienced HR leaders will share how they have reshaped their HR analytics from reporting factories to strategic solution providers that answer some of the most important business…Continue
Added by Alesia on December 4, 2014 at 2:00pm — No Comments
As a product manager in the domain of predictive analytics, I own the responsibility to build predictive analytics capabilities for consumer facing and/or enterprise platforms; the business applications vary among item recommendations for consumers, prediction of event outcomes based on classification models, demand forecasting for supply optimization, and so on. We usually see the applications where the predictive model built using machine learning technique(s) is leveraged to score the new…Continue
Added by Ram Sangireddy on October 6, 2014 at 5:53pm — No Comments
How will Advanced & Predictive Analytics (APA) affect you? Our inaugural Advanced and Predictive Analytics report can help answer that question! APA is growing and developing a plan for your organization now is critical!
The 2014 Wisdom of Crowds® Advanced and Predictive Analytics market study contains everything you need to assess this dynamic market…Continue
Added by Michael Walker on July 23, 2014 at 2:30pm — No Comments
Leonard Baum and Lloyd Welch designed a probabilistic modelling algorithm to detect patterns in Hidden Markov Processes. They built upon the theory of probabilistic functions of a …Continue
Both R & Python should be measured based on their effectiveness in advanced analytics & data science. Initially, as a new comer in data science field we spend good amount of time to understand the pros and cons of these two. I too carried out this study solely for “self” to decide which tool should i pick to get in depth of data science. Eventually, i have started realizing that both (R & Python) has its space of mastery along with their broad support to data science. Here some…Continue
NFL 2013 Team Expected Points Added (EPA) per game - Defense by Offense
The atavistic love of sport, strategy,…Continue
Added by Michael Walker on January 27, 2014 at 7:00pm — No Comments
One important goal of data science is to help decision makers make better decisions. Markov…Continue