This Checklist discusses seven best practices for implementing data warehouse automation within an agile development framework.
This Checklist discusses seven key considerations to help organizations focus their evaluation and develop a strategy for gaining value from open source technologies to support faster, more powerful, and more flexible analytics.
This TDWI Checklist Report drills into seven recommendations and discusses many of the new vendor product types, their functionality, and user best practices that can contribute to data integration modernization. It also presents the business case and technology strengths of each recommendation.
Download this e-book to read articles, opinions, and interviews that can guide your approach to understanding and employing data warehouse automation.
Download this e-book to read articles, opinions, and interviews that can guide your approach to understanding and implementing predictive analytics.
To help the reader understand the ongoing evolution of data management—in response to new requirements around big data and analytics—this report provides a checklist of data management practice areas that are most affected. In addition, the report relates new practices to existing ones, indicating when to use which one.
This Checklist Report discusses what your enterprise should consider before diving into a data lake project, no matter if it’s your first or second or even third major data lake project. Presumably, adherence to these principles will become second nature to the data lake team and they will even improve upon them at some point.
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