A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. It is a system or repository of data stored in its natural/raw format, usually object blobs or files. A data lake can store relational data from line of business applications, and non-relational data from mobile apps, IoT devices, and social media. It can include structured data from relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs) and binary data (images, audio, video) . Data lakes allow you to import any amount of data that can come in real-time, and store any type or volume of data in full fidelity.
Unlike most databases and data warehouses, data lakes can process all data types, including unstructured and semi-structured data like images, video, audio, and documents, which are critical for today’s machine learning and advanced analytics use cases. Data lakes provide a foundation for data science and advanced analytics applications, enabling organizations to manage business operations more effectively and identify business trends and opportunities.
In summary, a data lake is a centralized repository designed to store, process, and secure large amounts of structured, semi-structured, and unstructured data in its native format until it is needed for analytics applications.
