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Any organization can become data-centric by taking advantage of some of the emerging trends discussed in this checklist. This report reviews some of the practices adopted by data-centric organizations and suggests ways to learn from their experiences.
This TDWI Best Practices Report focuses on the emerging world of BI and analytics in the age of AI and big data. The research explores organizations’ satisfaction with current technologies and the issues driving interest in newer solutions that enable organizations to exploit advances in AI and big data.
This TDWI Checklist report drills down into the adjustments and optimizations in data quality practices required for big data.
This TDWI Checklist focuses on how organizations can develop strategies for improving operational intelligence, particularly by realizing value from IoT data.
This TDWI Checklist Report discusses three broad areas of best practices for helping to make machine learning, and those involved with it, successful.
In this checklist, we explore the concept of hybrid transaction/analytical processing (HTAP), an alternative architecture that enables analytics to be performed in concert with transaction processing. We will present best practices for taking advantage of this alternative architecture to enable real-time analytics.
In addition to automation using AI, next-generation data catalogs often contain new features such as crowdsourcing and collaboration. This TDWI Checklist describes five ways modern data catalogs drive business value.
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