Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping a toe: Integrating a legacy data warehouse into a data lake leverages the structured systems that have been ...

If you’re even tangentially involved with big data, you know that finding storage solutions for the volumes of data being generated every second is of utmost importance. When it comes to managing data ...

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The true measure of an effective data warehouse is how much key business stakeholders trust the data that is stored within. To achieve certain levels of data trustworthiness, data quality strategies ...

Enterprise data warehouses, or EDWs, are unified databases for all historical data across an enterprise, optimized for analytics. These days, organizations implementing data warehouses often consider ...

Data warehouses may seem like a trip down memory lane, or just a clunky data store. But if we look closely at data warehouse projects, the goals - and results - remain relevant. Most clients I speak ...

Essentially, a data warehouse is an analytic database, usually relational, that is created from two or more data sources, typically to store historical data, which may have a scale of petabytes. Data ...