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97 things every data engineer should know

Grouparoo

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. Open question: how to seed data in a staging environment? Test system with A/A test. Be adaptable.

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Creating Value With a Data-Centric Culture: Essential Capabilities to Treat Data as a Product

Ascend.io

Treating data as a product is more than a concept; it’s a paradigm shift that can significantly elevate the value that business intelligence and data-centric decision-making have on the business. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.

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Kickstart Your 2023 with these 6 Articles – The Meltano Teams Favorite Data Articles of 2022

Meltano

He compared the SQL + Jinja approach to the early PHP era… […] “If you take the dataframe-centric approach, you have much more “proper” objects, and programmatic abstractions and semantics around datasets, columns, and transformations.