DataOps Implementation Guide-01

DataOps For Big Data, ETL, Data Migration, Business Intelligence Reporting

Data-centric projects are becoming both bigger in size and complexity, which makes execution that much more difficult. This not only creates delays in project execution but also results in poor data quality. More and more projects are facing:

Longer time to Market – The time required for projects is increasing, with many cloud data migration projects having multi-year timelines.
Delayed or failed projects – Data teams are underestimating the complexity of the data projects resulting in last moment surprises as well as cost overruns.

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