Blogs

The 3 Cs of big data

The 3 Cs of big data

June 23, 2016 | by Chris Nott, Client Technical Leader for UK Public Sector, IBM UK Ltd.
Data scientists and others often encapsulate big data by its dimensions known as the four Vs: volume, variety, velocity and veracity. But when considering big data as a source for insight to enhance decision making, it may be best characterized by its three Cs—confidence, context and choice—with...
Keep your head above water with information lifecycle governance

Keep your head above water with information lifecycle governance

June 21, 2016 | by Nadine Noreldin, Esq., Content Marketing Manager, Information Lifecycle Governance (ILG), IBM
Ubiquitous data is so easily generated, and for that reason many enterprises today are exceedingly challenged to handle it all successfully. Take a look at a comprehensive information lifecycle governance solution that can help prevent enterprises from becoming submerged in their own sea of data.
Cloud-based ingestion: The future is here

Cloud-based ingestion: The future is here

June 20, 2016 | by Roger Welch, Solution Architect for WW COC (Dragon Slayer), IBM
Cloud computing has been around for quite a while, and today it is characterized as a collaborative, secure and cost-effective platform largely fueled by Internet-based ecommerce. And while the analog processing of paper-based information may not yet be a thing of the past, see why cloud-based...
Don’t sweat the ROI: IBM + Box = time well spent

Don’t sweat the ROI: IBM + Box = time well spent

June 15, 2016 | by Deb Gonzalez, ECM Marketing Manager, IBM
Having to report on the return on investment of projects can be a headache. Check out a new resource that can arm you with a wealth of short, easy-to-consume, on-demand podcasts that showcase integrated Enterprise Content Management portfolio solutions with powerful, collaborative capabilities that...
The power of machine learning in Spark

The power of machine learning in Spark

June 13, 2016 | by Max Seiden, Lead Spark Engineer, Platfora
Spark’s built-in machine-learning library (MLlib) provides a key differentiator from predecessor open source technologies and leverages Spark’s distributed, in-memory execution model. Take a look at some practical applications for specific Spark machine-learning algorithms in three advanced...
How can data scientists collaborate to build business applications?

How can data scientists collaborate to build better business applications?

June 10, 2016 | by James Kobielus, Big Data Evangelist, IBM
We asked five social influencers how data scientists can collaborate to build better business applications. See what they had to say.
A DB2 release that doubles down on data protection

A DB2 release that doubles down on data protection

June 10, 2016 | by Roger Sanders, DB2 for LUW Offering Manager, IBM
Enterprise-scale database technology needs to be on its game when it comes to thwarting security threats and protecting data from loss because of disaster or system failure. Take a look at advanced security features built into IBM DB2 for Linux, Unix and Windows Version 11.1 that can help ensure...
InsightOut: The role of Apache Atlas in the open metadata ecosystem

InsightOut: The role of Apache Atlas in the open metadata ecosystem

Frameworks for open metadata and governance

June 10, 2016 | by Mandy Chessell, Distinguished Engineer, IBM Analytics Group CTO Office, IBM
What makes Apache Atlas different from other metadata solutions is that it is designed to ship with the platform where the data is stored. It is, in fact, a core component of the data platform.
Top analytics tools in 2016

Top analytics tools in 2016

June 10, 2016 | by Gaurav Vohra, CEO & Co-Founder, Jigsaw Academy, The Online School of Analytics
Join us for a look at what’s on the horizon in data analytics, discovering how a broad array of tools aims to change the way we do—and think about—data science.
End-to-end analytics in the cloud

End-to-end analytics in the cloud

June 9, 2016 | by John J. Thomas, Distinguished Engineer and Director, IBM Competitive Project Office, IBM
Deriving actionable insight from data and analytics is shifting to unified, cloud-based platforms that can be used by a variety of analysis personas. Take a look at a national retail chain scenario demonstrating how a comprehensive portfolio of end-to-end analytics in the cloud can provide the...

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