DataOps is a principle that focuses on increasing the quantity and quality of data deliveries while reducing cycle time. This is possible through using agile methods, improving collaboration within the organization and focusing on automation and monitoring.
DataOps sets a framework for how the development of data pipelines should take place in a changing world where continuous development and delivery of data is expected. This is done by addressing both organizational and technical challenges, as the framework defines principles for technical best practice, workflow, culture and data architecture.
DataOps combines agile development, DevOps and lean manufacturing and adapts them to the development and operation of data pipelines.
The agile approach is about working smarter by continuously involving the end user in the development of data flows and accepting feedback. Through this method, you can quickly respond to customer requirements and accelerate changes that lead to value and thereby increase overall efficiency.
DevOps focuses on the connection between development and operation. Data pipelines are to be developed as version-controlled code, and the goal is continuous deliveries to the business, with short development pressures. Reuse and automation of code ensures faster development, while monitoring increases quality. This results in reduced time to implementation, reduced time to market, minimized defects and reduced time to resolve issues.
Lean manufacturing helps to keep the focus on quality using tools such as statistical process control for data analysis.
By combining the above principles, DataOps can act as a framework for managing and automating data projects. By focusing on involving the end user and thereby creating an iterative process, you can ensure high-quality data, which ultimately leads to successful insights and useful information for the business.
Cegal uses the DataOps principles in more and more large data warehouse projects with our customers, as DataOps improves the quality and reduces the cycle time for data analysis. At Cegal we offer a full service stack around data pipelines and data lakehouse with the DataOps approach as a delivery model.