Blogs

Data visualization playbook: Determining the right level of detail

Data visualization playbook: Determining the right level of detail

August 31, 2015 | by Jennifer Shin
The most efficient way for data scientists to convey vital information is through visualizations—but if they aren’t easily understood, critical insights may become lost. Here’s a quick and handy guide to creating data visualizations that are appropriately detailed to ensure maximum effectiveness.
The strategic impact of predictive analytics

The strategic impact of predictive analytics

August 27, 2015 | by Kenneth Jensen, Senior Managing Consultant, IBM
Predictive analytics can transform your organization by helping you compete more effectively, grow sales revenues, retain customers, discover new customers, prevent fraud, improve operations and much more—but to achieve these strategic impacts, it’s best to think big, start small and act fast.
Why we need a methodology for data science

Why we need a methodology for data science

August 24, 2015 | by John Rollins, Chief Data Miner, Analytic Solutions Team, Netezza, an IBM Company
No less than traditional scientists, data scientists need a guiding strategy for solving problems. Such a methodology should directly address the problem at hand and should provide a framework for obtaining answers and results. Learn more about the Foundational Methodology for Data Science and how...
Applying data analytics to personalize care for every cancer patient

Applying data analytics to personalize care for every cancer patient

August 19, 2015 | by Bernhard Warner, Veteran Journalist and Partner, StoryTK
Medical experts agree that personalized care is integral to the fight against cancer, but providing such care is easier said than done when more than 14 million people are diagnosed with cancer each year. In this podcast, hear how one of the world’s leading cancer researchers plans to use big data...
Top 5 trends that are making life easier for data professionals

Top 5 trends that are making life easier for data professionals

August 7, 2015 | by Kimberly Madia, Worldwide Product Marketing Manager, InfoSphere Streams, IBM
An ever-changing business environment is forcing data professionals to rethink their work methods—but fortunately, help is available. Here are five trends that are making life easier for data professionals: the emergence of Apache Spark, opportunities for greater skill reuse, growth in online and...

How Spark is tuning up the logical data warehouse

July 21, 2015 | by James Kobielus, Big Data Evangelist, IBM
Apache Spark will become a core technology in the logical data warehouse (LDW), and its sweet spot is as the workbench of choice for data scientists who interactively and iteratively explore, build and tune statistical models for machine learning, graph and streaming analytics.
Answers to your questions about becoming a digital business

Answers to your questions about becoming a digital business

July 20, 2015 | by Louis Cherian, Digital Marketing Manager, Big Data & Analytics, IBM
How do you define a digital business? We organized a recent CrowdChat to discuss advantages, disadvantages, infrastructure needs, analytics, security and other key concerns for digital business. The participants, who included industry experts, also talked about how organizations need to change to...
Measuring the artificial intelligence quotient

Measuring the artificial intelligence quotient

July 9, 2015 | by James Kobielus, Big Data Evangelist, IBM
If we’re going to do the Turing Test right, we might as well use the same intelligence tests we apply to humans. Only by doing so will we ever have a sound basis for claiming that machine are more (or less) intelligent than people.
The new world of digital business

The new world of digital business

July 6, 2015 | by Mark Simmonds, Senior Product Marketing Manager, IBM
The digital business of tomorrow is a lot closer than you think—in fact, it’s already here and it’s beckoning you to take a closer look and see the wonders it has to offer.
Applying the big data and analytics maturity model for a competitive advantage

Applying the big data and analytics maturity model for a competitive advantage

July 6, 2015 | by Niall Betteridge, Executive IT Architect, IBM
Speed of insight is the most valuable characteristic for business competitiveness. However, the pace at which new technologies such as the Internet of Things and cognitive computing are being introduced poses further challenges to an enterprise’s ability to quickly accommodate and make use of new...

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