Agile development methods—as applied in data disciplines—have experienced strong adoption by users in recent years, and for good reason. As more organizations “run the business” based purely on data (and compete and innovate), data management professionals are under increasing pressure to deploy data solutions into business use sooner, produce multiple solutions, and align data solutions with quickly evolving business goals. Hence, delivery speed, development productivity, and business alignment are the leading priorities (and benefits) for agile data management.
There are multiple approaches to agility; some work well with specific IT disciplines while others don’t. When it comes to data integration solutions, TDWI has seen a number of agile methods work consistently well across a wide range of organizations and application scenarios. These include the three pillars of agile data integration, namely: self-service data integration, rapid data set prototyping, and data stewardship or governance.
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