A data lake is a centralized repository for managing extremely large data volumes. It serves as a foundation for collecting and analyzing structured, semistructured, and unstructured data in its native format to drive new insights, better predictions, and improved optimization. Unlike traditional data warehouses, data lakes can process video, audio, logs, texts, social media, sensor data and documents to power apps, analytics, and AI. Data lakes can be built as part of a data fabric architecture to provide the right data, at the right time, regardless of where it is resides.
Check out IBM's Data Management Solutions → https://ibm.biz/data-mgmt-solutions Have you ever thought about how the process of moving food ingredients from farm to table could relate to how organizations store and eventually evaluate data – through data lakes, data warehouses and now a trending architecture, known as data lakehouse? In this video, Luv Aggarwal explains that analogy, and how a data lakehouse delivers on the benefits of data lakes and warehouses, and more! Get started for free on IBM Cloud → https://ibm.biz/ibm-cloud-sign-up
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