Each insight is useful for only a limited amount of time, so organizations that don’t closely track their insights’ shelf lives may be making poor decisions because of outdated information. Learn how to fix this.
For decades, a company’s database usually had a single job: operating as either an operational — also known as transactional — database or acting as a data warehouse. It was also typically deployed in a single location: on premises. Today, companies not only want more from their databases, but also
If your organization is trying to make the most of its analytics capabilities, don’t miss these IBM Insight sessions—a presentation and a super session offering a deep look into the world of real-time analytics and discussing how to inject analytics into real-time operational systems.
Using Twitter data and IBM analytics, telecommunications companies can fine-tune their churn models, better understand the products and services that their customers truly value and present existing customers with compelling offers—potentially recovering millions in lost revenue.
Where would today’s world be without streaming data? We depend on it for everything from entertainment to business analysis. And unlike the batch days of old, visual analytics tools are available to help process the growing amount of streaming data in real time.
For insurance companies, the integration of big data and analytics solutions with telematics technologies offers important opportunities to extend the use of telematics data beyond usage-based insurance (UBI) and improve competitive differentiation.
IT infrastructure—it's at the core of everything we do and who we are. Imagine a world without infrastructure: humans would be amorphous blobs, buildings would crumble, cities would be chaos. But, luckily for us, infrastructure does exist and it is the cornerstone of business. However, it's not
At Wednesday morning’s IBM Insight general session, IBM revealed hugely exciting new advancements they’ve been making in big data and analytics technologies. After presenting a use case on how IBM’s G2 Sensemaking engine is successfully being used to stop piracy in Southeast Asian Seas, conference
Where the Canadian National Railway used to rely on monthly data reports, they now operate more efficiently—in near-real time—with predictive analytics. IBM PureData for Analytics has enabled the company to apply logical insights from their data to save fuel consumption, predict shipments and keep
Phillippe Chartier, information delivery team lead at Canadian National Railway and this week's Big Data & Analytics Hero, tells us how they used to rely on monthly data reports, but now they operate more efficiently—in near real time—with predictive analytics. Canadian national Railway applies
IBM Predictive Customer Intelligence solutions helps provide a consistent and profitable experience across all channels including marketing outreach, sales and customer service; and across all touch points whether online, through a call center, mobile apps, social media or in a store.
If day one at IBM Impact centered on the Composable Business, day two seems to have focused on one of its key enabling components: Real-time Actionable Insight.
Yesterday, IBM SVP Robert Leblanc declared, “companies today need to treat cloud as a growth engine, reinvent their mobile experiences
Whether you call it stream computing, data in motion or real-time data, there’s no doubt that one of the most important aspects of big data is being able to capture, process and analyze data as it is happening. This is the velocity component of anybody’s definition of big data.
Unlike data that’s