One of Fabric’s key characteristics is that it is lake-centric. All of its data is stored in a data lake—OneLake. This chapter will walk you through the basics of data lakes and the specifics of OneLake.
Overview of Data Lakes
A data lake is a centralized repository that allows for the storage of structured, semi-structured, and unstructured data at any scale. Unlike traditional data warehouses that store data in predefined schemas, data lakes are designed to hold vast amounts of raw data in its native format until it is needed. This flexibility supports diverse data types including text, images, videos, and social media streams, making data lakes an integral part of modern big data architectures.
The primary purpose of a data lake is to provide a scalable and cost-effective solution for storing large volumes of data. This data can be processed and analyzed to extract valuable insights, facilitate real-time analytics, and support data science and machine learning applications. The structure of a data lake allows businesses to store all their data in one place, enabling comprehensive analysis and integration across different data sources.
Evolution of Data Storage Solutions
Data storage solutions have evolved significantly over the years, reflecting the growing complexity and scale of data management needs.
Figure 3-1 shows how data storage solutions have developed over time.
Figure 3-1. The evolution of data storage systems
The journey ...
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