Intel® oneAPI Data Analytics Library (oneDAL) is a library that helps speed up big data analysis by providing highly optimized algorithmic building blocks for all stages of data analytics (preprocessing, transformation, analysis, modeling, validation, and decision making) in batch, online, and distributed processing modes of computation.

The library optimizes data ingestion along with algorithmic computation to increase throughput and scalability. It includes C++ and Java* APIs and connectors to popular data sources such as Spark* and Hadoop*. Python* wrappers for oneDAL are part of Intel Distribution for Python.

In addition to classic features, oneDAL provides DPC++ SYCL API extensions to the traditional C++ interface and enables GPU usage for some algorithms.

The library is particularly useful for distributed computation. It provides a full set of building blocks for distributed algorithms that are independent from any communication layer. This allows users to construct fast and scalable distributed applications using user-preferable communication means.

For the complete list of features, documentation, code samples, and downloads, visit the official Intel oneAPI Data Analytics Library website. If you plan to use oneDAL as part of the oneAPI Base Toolkit, consider that priority support is available as a paid option. For Intel community-support, visit the oneDAL forum. For the community-supported open-source version, visit the oneDAL GitHub* page.