Did you know that the convenience and speed of mobile is now applied to the work of policing? Criminals are often experts at utilizing technology to commit crime. Now our police officers have mobile speed and ease of use to help them make data-driven decisions on the front lines.
In part seven of this series, we looked at the second key stage within the analytics lifecycle (Analyze), which focuses on analyzing the data and identifying the insights most likely to create a positive business impact. In part eight we will examine recommendations and practical actions for the
Describing intelligence software has gotten a whole lot easier as Hollywood continues to produce gripping spy shows like The Blacklist, Homeland and CSI. But while the layman description may have gotten easier, the real threatscape continues to evolve as criminal and terrorist networks continue to
Deep learning algorithms are growing progressively smarter at recognizing patterns in video, audio, speech, image, sensor and other non-textual data objects. Correlation of deep learning model results with other sources of contextual information can show how the information supplied by media and
According to Gartner, digital business is the “creation of new business designs by blurring the digital and physical worlds." There are three key foundational shifts that are making the digital business phenomenon real. Interestingly, these tectonic shifts are also driving faster adoption of
With a lot of moving parts, CEVA was generating a lot of content. Pulling it all together provided flexibility and insight into the content CEVA already had. With IBM solutions, CEVA now has the data it needs to start driving key decision making for the future.
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Safety Insurance Company had the common problem of too many databases. There was no single version of the truth, and this led to inconsistent answers across the enterprise. With IBM solutions, the organization now has one repository for all its data and the power to use big data to fight fraud.
In part six of this series, we finished our exploration of the first of three key stages within the analytics lifecycle (Acquire) and suggested recommendations and practical actions for that stage. In part seven we will look at the study’s second key stage within the analytics lifecycle, Analyze,
Many companies today have already begun leveraging their big data to gain a competitive edge. As the world's new natural resource, big data can drive business decisions and catapult organizations to the top of their industry. IBM is helping businesses make sense of all that data.
IBM i2 Enterprise Insight Analysis integrates IBM's best in class big data and advanced analytics capabilities to enable cross-sector organizations to turn overwhelming data into actionable intelligence, in near real time.
Competitive features include: Multi-dimensional visual analytics, a 24/7
Not everyone can be a data analyst, but IBM DataWorks makes the numbers less scary for business users. With a more refined approach to big data, everyone can use this information to make crucial decisions to add value to any business.
Download: The top 5 ways to get started with big data
It’s that time of the year again: when fans begin lining up at the supermarkets to plan football weekend festivities. Let's take a look at how can predictive analytics be used in analyzing everything from performance to parking at the big event.
In part five of this series we explored Acquire, the first of three key stages within the analytics lifecycle, which provides the ability to acquire and integrate data quickly—foundational to creating an analytics speed advantage. In part six we will look at recommendations and practical actions