Checklist: Achieving Scale and Simplicity in Data Engineering: Five Best Practices
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Robust data engineering processes ensure that analytics are always accurate, relevant, and fit for purpose.
Making the most of your enterprise data requires a high-performance pipeline that transforms it all into ready-to-use business assets.
Essentially, a data pipeline is a chain of connected processes that takes data from sources and prepares it for downstream data and analytics applications to consume (by transforming, integrating, cleansing, augmenting, and enriching the data). How can you simplify the deployment and management of your data pipelines, even as they span the most complex, distributed cloud environments?
This TDWI Checklist discusses key steps for deploying and operating cloud-based data pipelines.