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TDWI Articles

Data Digest: Use Unstructured Data, Check Your Strategy, Importance of Integration

Is your unstructured data siloed, your strategy unclear, or your big data inaccessible? These issues may be holding your enterprise back.

Top Trends in BI and Self-Service Visual Analytics

Organizations need to seek the right balance of freedom and oversight that enable users to get their work done self-service style. Here are four trends that will help organizations achieve that goal in 2017.

Interest in Spark Shows No Signs of Cooling Off

The Apache Spark cluster computing framework is widely used in the enterprise, and most adopters expect to increase their use of Spark over the next year, according to a recent survey of big data professionals.

Data Digest: Cost of Poor Data Quality, Security for Digital Disruptors, Removing Data Silos

How much unrefined data may start costing enterprises, why a disruptive business strategy requires data security, and why some enterprises are still unwilling to let go of departmental data silos.

7 Vendors at Strata/Hadoop World 2016: First Impressions

Fern Halper, vice president and senior director of TDWI research for advanced analytics, offers her perspective on announcements from seven vendors.

Necessity, Not Luxury: Automating Testing and Quality Assurance for BI

It was hard enough to manage testing and quality assurance in the old days. In the context of big data, cloud, streaming data, and other still-emerging technologies, automated testing and quality assurance is a necessity, not a luxury.

Data Digest: Protect IoT, IoT Data Integration, Why Choose Self-Service

Learn how to protect your IoT devices from attacks, how to prepare data integration strategies for IoT, and why enterprises are choosing self-service analytics tools.

Overcoming Patchwork Data Prep

In their work, many data and business analysts spend the bulk of their time on data preparation tasks using a patchwork of tools. I visited with Manan Goel of Paxata to discuss how to reduce this overhead, how to weave together basic and advanced data preparation capabilities, and how analysts can be more efficient and effective in their work.

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