Data Lake vs. Data Warehouse –
A Modern Data Strategy Debate
Today, organizations are becoming more data-driven by using their data to build new products, stay ahead of the competition and provide better customer experiences. As a result, data management and processing it for various stakeholders needs to be fast, automated, and scalable.
Organisations currently collect and process data in a manner that allows them to make the decision making process simpler, helping them gaze at the past, manage the present and predict the future. Data warehouse supports analysis of operational system data for BI, while data lakes support newer use cases that leverage data for machine learning, predictions, and real-time analysis.
The question is: does your business need both and why?
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