Blogs

Case in point: Verizon’s cognitive journey and the customer experience

December 15, 2016 | by Preetam Kumar, Product Marketing Manager, IBM Analytics, IBM
Without question, our lives are very different from only a couple decades ago, thanks in part to some pretty amazing technology advances including smartphones and other devices, mobile apps, an ever-growing array of social channels and more. Take a look at how one telecommunications organization...
10 reasons to be excited about data analytics in 2017

10 reasons to be excited about data analytics in 2017

December 15, 2016 | by Jen Underwood, Founder, Impact Analytix, LLC
What does 2017 hold for the many-faceted world of data analytics? Explore these predictions as you prepare to follow hard on the heels of data innovation throughout 2017.
Hadoop and Spark coaches: Training and insights for all maturity levels

Hadoop and Spark coaches: Training and insights for all maturity levels

December 15, 2016 | by Andrea Braida, Portfolio Marketing Manager, IBM
At the core of many big data architectures is Apache Hadoop and Apache Spark. Organizations adopting these technologies for their big data journey are nevertheless at different levels of maturity. Hear what Prasad Pandit had to say in an interview with Andrea Braida about how IBM is evolving its...
What successful GDPR strategies have in common

What successful GDPR strategies have in common

December 14, 2016 | by Christophe De Melio, Strategic Client Engagement Executive, Analytics CTO Office, IBM
IBM Insight at World of Watson 2016 had a lot of worldwide focus on cognitive capabilities and their application in analytics, commerce and security. And yet, the General Data Protection Regulation (GDPR) adopted in 2016 and applicable in 2018, seemed to garner quite a bit of interest among...
The future of big data lies in integration

The future of big data lies in integration

December 13, 2016 | by Ronald van Loon, Director, Adversitement
The concept of big data fabric represents a fundamental change in how businesses approach data storage, fast data analytics, and streaming data to make it much easier, faster, and simpler to retrieve actionable information and increase the value that you can get from customer data.
Dark data: The elusive black swan and financial fraud, part 1

Dark data: The elusive black swan and financial fraud, part 1

December 13, 2016 | by Michael Maxwell, Offering Management, IBM
Incumbent fraud-detection models just aren’t up to the task of revealing black swans in high-value payment channels managed by financial institutions. See how the key to identifying the fraudulent activity that is a black swan in your flock comes down to understanding and spotting the deviations of...
Machine learning: The big draw at a big Beijing, China event

Machine learning: The big draw at a big Beijing, China event

December 12, 2016 | by Steve Moore, Senior Story Strategist, IBM
One thing that a recent event in Beijing, China confirmed is there’s no shortage of interest in machine learning for developers in that region. Take a look at snapshots of event highlights featuring rich content on artificial intelligence, cognitive capabilities, machine learning and more presented...

Information architecture: The key to governance, integration and automation

December 12, 2016 | by Elizabeth Koumpan, Executive Architect, IBM
Emerging technologies—3D printing, cloud computing, the Internet of Things, mobile computing, sensors, wearable devices and the like—are transforming the ways in which modern organizations manage and use data. But much of that data remains unused. Successfully capitalizing on information...
Can Master Data Management and entity analytics be self-service?

Can Master Data Management and entity analytics be self-service?

December 12, 2016 | by Jay Limburn, Senior Technical Staff Member and Offering Manager, IBM
Historically, Master Data Management (MDM) projects have focused on creating a single view of the truth that can be consumed by business processes. Learn more about how the evolving need to utilize MDM serves as catalyst for a new solution extension offering a managed data preparation and data...
Sales performance management and C-level goals

Sales performance management and C-level goals

December 9, 2016 | by Mark Donnolo, Founder and Managing Partner, SalesGlobe
Before diving into planning for sales compensation, get a fix on the company’s business goals and strategy. See why having a framework in place is critical when designing a sales strategy and compensation program.