October 2014, Forrester Consulting worked with IBM on a commissioned study to analyze the total economic impact that IBM’s Information Management solutions have on three specific big data use cases to help its customers solve important business problems.
Optimize Operations and Reduce Fraud
Data is growing at an accelerated pace and users are demanding better access to data, but business users grab what’s available, not what’s best.
Learn more about data refinement and evolve the way the world works with data.
In India, the business of matchmaking is fast evolving. The traditional practice which was once strictly managed through family connections and word of mouth, is fast evolving to include mobile and social technology, becoming the medium of choice for meeting potential partners. With over 8000 new subscribers added daily, Matrimony.com is one of the fastest growing matrimony internet conglomerates in the world with a presence in India and across South Asia, the UK, US, Dubai, Sri Lanka & Malaysia.
IBM is delivering new software that allows organizations to gain better visibility and take a more proactive, holistic approach to countering fraud. This includes the ability to aggregate Big Data across a variety of internal and external sources – including mobile, social and online – and apply sophisticated analytics that continuously monitor for fraudulent indicators.
Using big data and analytics to link insights to action can improve business process optimization and asset productivity to increase efficiencies.
This infographic touches on five critical steps that will help customers streamline their application infrastructure, reduce infrastructure costs and transform enterprise data into a trusted, high-value resource by successfully consolidating and retiring their applications.
Machine data is all around us: logs, sensors, GPS devices and meters to name a few. The enormous growth of machine data has become a major driver of big data solutions and a challenge for many organizations. The complex and diverse nature of machine data leaves many organizations unable to leverage it. Yet without it, they’re making business decisions on a fraction of the information available to them.