Blogs

Top 10 IBM Big Data & Analytics Hub blog posts of 2017

Top 10 IBM Big Data & Analytics Hub blog posts of 2017

December 4, 2017 | by Erika Ulring, Editor-in-Chief of the Big Data and Analytics Hub, IBM
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....
Compliant data freedom: Oxymoron or opportunity?

Compliant data freedom: Oxymoron or opportunity?

November 28, 2017 | by Ron Reuben, Offering Manager, IBM Analytics
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...
Driving breakthrough innovation and change

Driving breakthrough innovation and change

To achieve differentiation and speed to market, businesses need to innovate and drive change.

November 27, 2017 | by Steve Astorino, Vice President, Development, IBM Private Cloud Analytics Platform
Speed to market and differentiation are two key factors for business success. To achieve both, organizations need to rapidly innovate and drive change.
Data Science for All: What is it? Why care? How do I get it?

Data Science for all: What is it? Why care? How do I get it?

November 17, 2017 | by William Roberts, Technical Product Marketer, IBM
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.
IBM launches new Integrated Analytics System with Machine Learning

IBM launches new Integrated Analytics System with Machine Learning

November 16, 2017 | by Charles King, Principal Analyst and President, Pund-IT, Inc.
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.
5 tips for machine learning success outside of Silicon Valley

5 tips for machine learning success outside of Silicon Valley

November 15, 2017 | by Jean-François Puget, Chief Architect – Analytics Solutions, IBM
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...
Learning machine learning? Six articles you don’t want to miss

Learning machine learning? Six articles you don’t want to miss

September 28, 2017 | by Dinesh Nirmal, Vice President, Analytics Development, IBM
Digital disruption has revolutionized the way we live and do business — and machine learning is the latest wave of that revolution.

Transforming governance in the insights era

September 28, 2017 | by Ron Reuben, Offering Manager, IBM Analytics
There’s a revolution taking place within information governance. This change is driven by the growing needs of business users, and the recognition that trusted, high-quality, easy-to-find data can be the differentiator that drives better business outcomes.  
How to succeed in the multi-cloud era

How to succeed in the multi-cloud era

September 26, 2017 | by Benjamin Tao, VP, Worldwide Portfolio Marketing, IBM Analytics, IBM
In a time when data is perhaps a business’s most valuable resource, the ability to access, protect and analyze information plays a critical role in an organization’s overall multi-cloud strategy. Here's how to succeed.
When faster data science moves the world

When faster data science moves the world

September 26, 2017 | by Noah Kuttler, Marketing, IBM Data Warehouse Offerings, IBM
Learn how the IBM Integrated Analytics System, a unified data platform built on the IBM Common SQL Engine, helps do data science faster with high performance, embedded machine learning capabilities and built-in tools for data scientists to deliver analytics critical to increasing your organization’...