Data has become indispensable to gaining a competitive edge. Still, many data warehouses pose a challenge for organizations trying to manage large datasets: only a fraction of data is available for analysis. We call this the “dark data problem,” where existing data warehouses are too complex, slow or expensive to extract value. A modern data warehouse can solve these types of problems. Modern solutions support rapid data growth, interactive analytics, relational, non-relational, and streaming data types, all leveraging a single, easy-to-use interface. They offer a common architectural platform for newer technologies while accommodating legacy ones. This can be the key to unlocking deeper business insights for organizations.
Key elements of a modern data warehouse:
Data ingestion: take advantage of relational, non-relational, and streaming data sources
Federated querying: ability to run a query across heterogeneous sources of data
Data consumption: support numerous types of analysis including ad-hoc exploration, predefined reporting/dashboards, predictive, and advanced analytics
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