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.

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Quality management

Sentiment or Sediment?

Governance of highly disposable social sentiment data can create a quality conundrum

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Trusting-big-data
Quality management

Trusting Big Data

Make business-critical decisions confidently without delay

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Building-confidence-in-big-data
Lifecycle management

Building Confidence in Big Data

IBM InfoSphere innovation empowers end users to understand and trust their data

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Context influences confidence in big data
Quality management

Context Influences Confidence in Big Data

Data managers can learn a lesson in confidence from a can of tuna

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Defending big data insight
Quality management

Defending Big Data Insight

Use integration and governance to establish trust

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Big Data at the Speed of Business
Quality management

Big Data at the Speed of Business

Broadcast event replay now available

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Data Warehousing 4
Integration and Governance

Keeping the Data in Your Warehouse Fresh

Introducing IBM InfoSphere Data Replication

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Quality management

Governance Over Critical Data Elements

10 industry examples that quantify its value

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Big Data and Warehousing

Big Data: A Boon For Governance Professionals

A strong big data governance program can take the guesswork out of finding and using the right information to make business decisions

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datacable
Integration and Governance

Governing Customer, Product, Network, and Big Data in Telecommunications

Best practices for managing industry-specific information

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governance_fi
Quality management

Why Governance Matters

IBM experts debate the promise and perils of data governance and why data quality should be a top concern

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Database management software

Taking the First Steps Toward Data Quality

The basics of defining a data quality program

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