Readers of the IBM Big Data & Analytics Hub were hungry for knowledge this year. They voraciously read blog posts about incorporating machine learning, choosing the best possible data model, determining how to make the most of data science skills, working with open source frameworks and more.
The data lake may be all about Apache Hadoop, but integrating operational data can be a challenge. Learn how to deliver real-time feeds of transactional data from mainframes and distributed environments directly into Hadoop clusters and make constantly changing data more available.
The new Gartner Magic Quadrant (MQ) for Master Data Management has been published, and what you might not notice at first glance is that this year, IBM chose not to participate. Gartner still included IBM in the MQ. However, we did decline to engage in the process and provide detailed data for
Many large organizations still have a large amounts of data on-premise, but also need data from a public cloud. Regardless of where the data resides, organizations can build a trusted data source from which they can drive key business insights and derive significant sustained advantages. Here's how.
I just wrapped up attending and keynoting at this year’s ARMA Live conference. We're moving towards not just bringing together the practices, benefits and mandates of security, privacy and information governance, but also seeing the benefits and opportunities of business results of ever more
Managing enterprise information has always been a good idea, however with the potential for looming penalties from the General Data Protection Regulation (GDPR) non-compliance, companies are waking up and some organizations are even seeing GDPR as an opportunity to establish strengthened
Organizations everywhere, from massive governments to the smallest start-ups, are in a race for the best-possible data expertise and tools. To help your team understand the data science journey, IBM created the Data Science for All webcast.
Information analytics has never been a “one size fits all” proposition. That applies to the hardware and software technologies organizations employ, the information being parsed and the goals of specific projects.
Machine learning concerns in Silicon Valley tend to be different from those elsewhere in the U.S. — and outside of the U.S. So, here are five tips for those hearing about machine learning efforts in Silicon Valley, but who work elsewhere. These suggestions consider where machine learning and data
In most modern-day organizations, external macros tend to be very influential — leaving little bandwidth for optimizing data governance. And, as stricter data storage and security compliance regulations come into play, it's becoming more and more critical for organizations to ensure they have the
Today’s most successful companies think differently about data governance. Recent Aberdeen research suggests that top-performing companies are those that create a more holistic approach to data governance, incorporating the right technologies, processes, skill sets and internal capabilities.
If you’re holding an event for the very first time, what helps you gauge its success? At IBM Analytics University, we turned to social media analytics. Here’s a summary of what we learned from the experts and from Watson Analytics for Social Media.
Although there are many new and emerging classes of data integration, quality and governance software tools available in the market, many large organizations are coming to the conclusion that they're best served by a single unified enterprise data integration, quality and governance platform that