Modern data pipeline networks are increasingly getting complicated and traditional data governance frameworks aren't scalable, leaving your DataOps teams with never-ending data management nightmares. Meanwhile, with advent of self-serve analytics platforms, you have 3X more users who directly interact with data. If you are facing frequent pipeline failures, low end-users' adoption and high time to develop an analytics solution, its time to modernize your data pipelines that feed your solutions.Modernize your data!
Often, organizations end up creating a complicated network of siloed data pipelines that costs more than they heal. With multi-functional data networks, you can achieve scale and speed with a quarter of unitary effort.
The difference between good data and bad data is a self-healing data pipeline. Considering them as a part of data systems modernization can help in the reduction of manual governance by 60% and time to issue resolution by half.
By integrating DataOps principles into data pipelines, organizations can ensure a more efficient, reliable, and scalable data infrastructure. It promotes the use of CI/CD practices in data pipelines, reducing errors and speeding up the process.
Modernize your data pipelines by coupling the latest software development practices with data engineering - containerization and orchestration of data pipelines, automated testing and monitoring, metadata driven automation, lake house architectures.