Data lake definition
A data lake is a centralized repository or system that stores, processes, and secures large amounts of data. It stores data in its raw format, which can be unstructured, semistructured, or structured. With a data lake, you can process all kinds of data, no matter the size or type. You don’t have to structure your data to store it in a data lake. Also, you can run different types of analytics on it, like dashboards, big data processing, visualization, machine learning, real-time analytics, and more.
See also: software repository, machine learning
Data lake elements
- Data movement. With a data lake, you can import as much data as you want. The data can come in real-time from multiple different sources and can be moved into the data lake in its original/raw format.
- Secure and store data. A data lake allows organizations to store all kinds of data, including data from databases, data from a line of business applications, data from mobile apps, data from IoT devices, and data from their social media platforms and apps. You also need to secure your data lake so that your data assets are protected.
- Analytics. With a data lake, organizations can access data with all kinds of tools and frameworks – whichever they prefer. Also, it allows you to run analytics without having to move your data somewhere else.
- Machine learning. You can generate all kinds of insights from your data lake, such as reports on historical data. Also, you can build models that forecast outcomes and suggest actions to achieve optimal results.
