Big Data Use Cases

Empowering athletes with real-time, data-driven decision support

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. Read More

An industry vertical analysis: Healthcare and big data

July 30, 2014
This new series covers big data adoption across multiple industrial sectors, as well as the defining big data elements and anomalies prevalent across each sector.  Read More

Big Data & Analytics Heroes: Nigel Hook

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. Read More

Get off the fence and get insight!

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. Read More

Blistering fast SQL access to your Hadoop data

July 28, 2014
In the rapidly evolving SQL-on-Hadoop space, IBM’s Big SQL 3.0 moves the industry forward through its contributions in improving query performance and workload management, while maintaining compatibility with open source Hive and SQL standard. This blog gets under the hood to explain how Big SQL 3.0 delivers these optimizations.   Read More

Capabilities for data archiving and application retirement

July 28, 2014
Gartner has recently released their first ever Magic Quadrant for Structure Data Archiving Application Retirement. In this report, Gartner evaluates vendors based on their capabilities and offerings for structured data archiving and application retirement. IBM has been recognized as a leader in the report. Read More

What banking can learn from retail

July 24, 2014
Banks can improve their reputation and gain consumer trust by emulating retailers and leveraging big data and analytics. Read More

Real-time healthcare compliance analytics can keep patients alive and well

July 24, 2014
Medical professionals are between the proverbial rock and hard place when trying to determine whether, how and why patients are failing to comply with doctor's orders. On the one hand, their ability to help people depends on having intimate, current and accurate knowledge of people's physical conditions and behaviors. On the other hand, doctors can't be Big Brother, engaging in 24x7 surveillance of their patients' private lives and wielding the power to punish recalcitrants. However, physicians can, within the bounds of privacy and propriety, use analytics to assess who might or might not be compliant. Using those insights, the healthcare system might identify the most appropriate real-time interventions to minimize the impacts of noncompliance on healthcare outcomes. Read More

Big Data & Analytics Heroes: Paula Post

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. Read More

Realize your data’s potential

July 18, 2014
Research indicates that business and IT professionals spend more than 70 percent of their time finding data, validating it or defending it, rather than focusing on what they find most important: analyzing the data. With too little time spent focusing on data analysis, organizations derive sub-optimal returns from their big data initiatives. For better business outcomes, and to maximize the value from big data, organizations need to invest in an agile data governance program.In a recent survey, respondents indicated that they spend more than 70 percent of their time finding data, validating it or defending it, rather than focusing on what they find most important: analyzing the data.  Read More

Pages