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Data Digest: Data Quality Challenges, Open Source Pros and Cons, Cloud Computing Definitions

Learn how to approach common data quality problems, what pros and cons you face selecting open source analytics solutions, and definitions of 20 common cloud computing terms.

Data Digest: Use Cognitive Computing with Big Data, Maintain Your Data Quality, Secure Your Big Data

Learn about trends in cognitive computing that help enterprises manage big data, why you may be struggling with data quality and what to do about it, and 5 best practices in big data security.

Data Digest: Fighting Terror with Big Data; Data Quality over Quantity, Increasing Big Data Value, Hiring the Perfect Data Scientist

Improve your data quality, get the most out of your big data projects, and hire a great data scientist with the tips in today’s articles.

Is Data Quality Stuck in the Dark Ages?

IT decision-makers weren't confident in the quality of their data 20 years ago, and they still aren't hopeful in 2016. Far from it, according to a new survey.

Data Preparation: Advanced Analytics to the Rescue

Demand is growing for faster, more dependable data preparation. According to a recent survey by TDWI, professionals believe there is plenty of room for improvement.

Data Digest: Managing Big Data Quality, Defining Insight, and Effective Analytics Tools

Explore governance principles to protect big data quality, the difference between analytics and insight, and tools for managing vast volumes of data.

Moving the Textual Analytics Cheese

There are plenty of natural obstacles to dealing with text, but those who feel threatened by advances in textual processing are inventing artificial obstacles as well.

Do You Understand the Knowns and Unknowns in Your Data?

Effective data preparation depends on recognizing how to handle what we know and what we don't know about a set of data. Our goal as analytics professionals is to make less unknown and more known.

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