Data Lake

Definition of Data Lake

Data Lake: A data lake is a term used in big data management to describe a storage repository that holds a large volume of raw data in its native format. The data in a data lake can be processed and analyzed by the business users who own it, without having to go through a central IT organization.

What is a Data Lake used for?

A data lake is a large, centralized repository for storing vast amounts of structured and unstructured data. This type of storage solution enables organizations to store and analyze information from multiple sources in its original format. Data lakes offer scalability, flexibility and cost savings compared to traditional database systems, allowing businesses to store data of any size, structure or format without the need for manual transformation.

Data lakes can be used in many different ways such as analyzing customer behavior patterns across multiple systems, identifying trends within large datasets or simply archiving mission-critical historical data. This type of storage system allows businesses to access information quicker and more easily than before while providing additional security measures that would otherwise be impossible with traditional databases.

In addition to providing faster access to data and greater security, a data lake also allows companies to gain insights into the larger picture by analyzing the relationships between different types of information. In this way, businesses can more easily identify correlations within their datasets while reducing the amount of time it takes them to investigate a particular problem area. Moreover, because most modern data lakes are built on open source platforms such as Hadoop, companies are able to take advantage of existing analytical tools and technologies which not only saves them time but also helps maximize their return on investment.