July 31, 2014
There are complex challenges that a data scientist might face in statistically modeling real-time decision-support scenarios in fast-moving athletic competitions. Each sport needs to be modeled on its own terms. A within-game decision-support predictive model for one sport cannot be applied directly to another sport, even ones that share a common ancestor or many surface similarities. No two sports have exact same "game evolution" structure, embody the exact same rules, play on the same surface, use the same equipment or generate the same types of performance data.
July 29, 2014
Nigel Hook, CEO at DataSkill and this week’s IBM Big Data and Analytics Hero, declares that they “are looking to use the new cognitive computing to really differentiate their customer’s ability to drive revenue.” He discusses how companies can really understand their patients and ultimately their customers to impact revenues.
July 29, 2014
In the world of big data, the elephant is king. Hadoop, whose elephant logo has become the face of big data, has been joined in the big data jungle by many friends: Pig, Jaql and even a ZooKeeper to keep them all in line. The entire big data jungle will be making a trip to Las Vegas in October for the world’s largest big data conference: IBM Insight.
July 22, 2014
Paula Post, group VP of merchandise optimization at BonTon Stores, Inc., indicates that with big data she is delivering to her workforce “true information so they can spend their time making decisions and doing things to drive the business.” Paula is this week’s IBM Big Data and Analytics Hero.
July 17, 2014
The recent controversy over the ethics of Facebook's attempts to influence moods through tweaks to its newsfeed algorithms is overblown. Essentially, Facebook data scientists conducted one of many real-world experiments that are standard operating procedure with them and with most online businesses these days. This was just a routine real-world experiment in big-data-driven sentiment analysis, content optimization and customer experience management.
July 17, 2014
Each month it seems like we hear automotive original equipment manufacturers (OEMs) reporting record growth, but what is driving this growth? Pent up demand? Attractive new products? Is the market actually growing, or could it be that the automotive industry is starting to use big data and analytics to better understand their customer, hat they want to buy, how they want to buy it and how they want to interact with their car and their car company?
July 15, 2014
“You can’t just look at one data source,” says Vince Walden, partner at Ernst & Young, and this week’s Big Data & Analytics hero. With so much data available to us today to get a clear picture businesses must be able to look “at the data in all different angles—upside down and sideways—to get to where we think the issues are in a case.”
July 10, 2014
As the quantified-self (QS) movement picks up steam, it will become more feasible to instrument more at-home infants with 24x7 physiological monitoring. It's increasingly feasible to cradle the baby's entire birth journey (prenatal, delivery, postnatal) in a comforting stream of vital signs, real-time alerts, prescriptive analytics and big data. The same QS-cradled infrastructure could conceivably serve as an early warning system throughout our lives.
July 9, 2014
IBM Analytics Warehouse for Bluemix is now generally available to all customers for your agile data warehousing and analytics needs. This pay-as-you-go cloud service, leveraging in-memory BLU technology, is designed to provide a single, agile in-memory platform for all applications required for most DW, BI and analytics projects.
July 8, 2014
Thod Nguyen, chief technology officer (CTO) at eHarmony and this week’s IBM Big Data & Analytics Hero, shares that “the faster we can actually have more insight to the data, the more we can actually feed that insight into our compatibility matching system to further improving our match quality.”