DataOps integration refers to the practice of applying DataOps methodologies to streamline and enhance the data analytics processes within an organization. This approach focuses on improving the quality and speed of data analytics by adopting principles similar to those found in DevOps, such as automation, agile orchestration, and continuous integration/continuous deployment (CI/CD).

By integrating DataOps, organizations can better manage their data pipelines, ensuring that they are adaptable to changes in business requirements and data sources. This integration allows for automated testing, version control, and quick auditability of changes, which collectively help in reducing errors and improving the overall efficiency of data operations. The goal is to transform data into business value, making it easier for analysts and data scientists to access and utilize data effectively.

To successfully implement DataOps integration, organizations should focus on the three aspects of the “Golden Triangle”: people, process, and technology, ensuring that all components work together harmoniously to maintain healthy data pipelines ²⁴.