In the era of exploding user engagement with customer-centric applications such as streaming services, online shopping, social media, and microblogging, enterprises are grappling with an ever-expanding volume of data. This deluge of data presents a challenge: how to efficiently store, process, and analyze it to provide customers with an enhanced experience. To navigate this data landscape and ensure timely access to information for informed decision-making, Data Lakes have turned to a key technique known as Data Partitioning.

Data partitioning is the technique of dividing extensive datasets into more manageable and logically structured components. Not only does it elevate data organization, but it also yields a significant enhancement in query performance.

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