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.

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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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

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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explore-new-frontiers-in-business-analytics
Strategies

Explore New Frontiers in Business Analytics

Converging basic and advanced analytics paves the way for keen insight and business innovation

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the-power-of-behavioral-fingerprinting
Technologies

The Power of Behavioral Fingerprinting

A big data application of online behavior detection is well suited for antifraud protection

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the-ground-truth-in-agile-machine-learning
Technologies

The Ground Truth in Agile Machine Learning

Distilling knowledge effortlessly from big data calls for collaborative human and algorithm engagement

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in-data-science-take-nothing-on-faith
Technologies

In Data Science, Take Nothing on Faith

Adopting a rigid regimen is required for vetting reproducible computational findings

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ibm-data-magazine-its-value-and-its-vision
Strategies

IBM Data Magazine: Its Value and Its Vision

A new course is set for an online publication with a rich tradition of serving the data management community

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