Data for the Enterprise
Data Operations (DataOps) is a methodology focused on the delivery of agile business intelligence (BI) and data science through the automation and orchestration of data integration and processing pipelines, incorporating improved data reliability and integrity via data monitoring and observability. DataOps has been part of the lexicon of the data market for almost a decade and takes inspiration from DevOps, which describes a set of tools, practices and philosophy used to support the continuous delivery of software applications in the face of constant changes.
Interest in DataOps is growing. Ventana Research asserts that by 2025, one-half of organizations will have adopted a DataOps approach to their data engineering processes, enabling them to be more flexible and agile. A variety of products, practices and processes enable DataOps, including products that support agile and continuous delivery of data analytics and continuous measurable improvement. An emphasis on agility, collaboration and automation separates DataOps from traditional approaches to data management, which were typically based on tools and practices that were batch-based, manual and rigid.