James Kobielus

James Kobielus is a big data evangelist at IBM and the editor in chief of IBM Data magazine. He is an industry veteran, a popular speaker, social media participant, and a thought leader in big data, Apache Hadoop, enterprise data warehousing, advanced analytics, business intelligence, data management, and next-best action technologies.

patterns-of-insight-and-expertise

Patterns of Insight and Expertise

Expertise can become a sustainable business resource if you bake it into your operational best practices for data management and analytics. Best practices are reusable patterns for guiding your quest for business results. The more complex your quest, the more urgently you need crisp patterns to help knowledge workers sift through everything for a sliver of useful intelligence. In IBM Data magazine the week of November 17, 2014, we have fresh discussions on access, search, and management patterns for unlocking …

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industrial-strength-data-management

Industrial-Strength Data Management

Organizations must manage their data with industrial discipline and repeatability.

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new-frontiers-new-insights

New Frontiers, New Insights

New frontiers sometimes emerge when we have new tools for exploring established frontiers.

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cognitive-computing-the-new-frontier-in-machine-intelligence
Strategies

Cognitive Computing: The New Frontier in Machine Intelligence

As cognitive systems such as Watson emulate modes of thought, will they extend innate, human cognition?

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welcome-to-the-new-data-forum

Welcome to the New Data Forum

What we have for you this week in IBM Data magazine is a significantly improved experience.

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big-data-era-opportunities

Big Data Era Opportunities

Analysts, researchers, data scientists, and other professionals face new challenges in the era of big data. But big data and analytics are opening up a lot of tremendous opportunities. In IBM Data magazine the week of October 20, 2014, new contributor Suresh Sane starts his two-part series on the past, present, and future of query-optimization best practices in the era of big data. Jennifer Shin provides the third of her four-part series on the US Food and Drug Administration’s open-data …

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ensembles-to-boost-machine-learning-effectiveness
Technologies

Ensembles to Boost Machine Learning Effectiveness

Employing ensemble-based crowdsourcing can confidently identify best-fit models

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focused-data-strategies

Focused Data Strategies

Robust data strategies are those that can surmount constraints, obstacles, disasters, and distractions without losing focus on their core objectives.

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Keeping Pace with Ever-Changing Data

Smarter businesses know they must flex their data strategies to align with new opportunities and challenges.

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datas-worth

Data’s Worth

Calculating data’s value depends on what type of data you’re focusing on.

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data-fluidity

Data Fluidity

Data is fluid with its own streams, lakes, and other facilities for holding, distributing, and filtering the precious resource.

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monetizing-a-crowdsourced-data-scientist-existence
Strategies

Monetizing a Crowdsourced Data Scientist Existence

Can project-oriented crowdsourcing initiatives put food on data scientists’ tables?

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