What Is a Data Lake?
Key Concepts and Benefits

According to Forbes, 95% of businesses grapple with managing unstructured data, while Forrester reports 73% of enterprise data goes unused for analytics.

With 94% of leaders yearning for more value from their data, the urgency to harness the power of data lakes has never been more important, especially in the age of AI. This article will show you how.

Data Lakehouse 101

Explore the basics of Salesforce Data Cloud, our customer data platform built on data lakehouse tech. This trail is a helpful guide that breaks it all down clearly.

Data lake vs. data warehouse vs. data lakehouse: key differences at a glance

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Data Lake FAQ

A data lake is a central repository of large volumes of data that’s stored in its original form. This data is typically raw and unprocessed, allowing for high flexibility as it doesn't require a predefined schema.

A data lake stores raw, unprocessed data for future analysis and diverse workloads, while a data warehouse stores structured, pre-processed data specifically optimized for traditional business intelligence and reporting queries.

Data lakes are highly versatile and can store virtually all types of data. This includes traditional structured data from databases, semi-structured data like XML and JSON files, and unstructured data such as text documents, images, and videos.

Benefits include immense flexibility to store diverse data, the ability to perform various types of analytics (including advanced machine learning), scalability for massive data volumes, and cost-effectiveness for storing large amounts of raw data.

Data in a data lake is primarily utilized for advanced analytics, machine learning model training, real-time data processing, and building cutting-edge data-driven applications. It supports exploration and discovery with raw data.

Challenges include ensuring data quality and preventing a "data swamp" (unorganized, unusable data), managing data security and access controls, establishing robust data governance, and effectively cataloging and discovering data within the lake.