This post was first published by MANTA, on their blog, and is reposted with permission

When we had data in one carefully controlled system, planning for change was simple. Today enterprises have data coming in from multiple sources, flowing through complex pipelines, and undergoing transformations across countless touchpoints. 

Unplanned, poorly communicated, and never-ending changes across the increasingly complex data environment threaten DataOps’ ability to drive meaningful progress and deliver business value. Teams get caught up in the twilight zone of two extremes—trying to move fast but breaking things or putting in the time yet falling behind. Sound familiar? 

Key Challenges For DataOps 

• Complexity and continuously shifting requirements prevent data teams from establishing a sustainable pace and project continuity.
• Inconsistent coordination and a lack of clear communication amongst stakeholders make building, deploying, and maintaining data pipelines unnecessarily difficult.
• Teams struggle with Increasing delays in operationalizing models due to a lack of quality data lineage.
• Without automated lineage data, analysts can spend hours manually cleaning and preparing data
• Data lineage solutions still require technical proficiency to leverage,making self-service impossible for business users.
• The lack of trust in data keeps efficient data availability and data democratization out of reach.

One Step Forward, Two Steps Back.

When DataOps teams have to manually trace data’s path across complex systems and hundreds of touchpoints, accuracy, and agility are the first casualties. By automating data lineage discovery, DataOps can transmute data chaos into data clarity and deliver a continuous, reliable stream of insights that bring value to the enterprise. 

With a lineage map of all the technologies, platforms, and tools that form the data pipeline, teams can end the vicious cycle of “one step forward, two steps back” and ensure that the security and integrity of their company’s data remain uncompromised across the entire pipeline. 

The Way To Successful DataOps in 2021 and Beyond  

Automated data lineage can empower DataOps teams to handle the challenges imposed by the growing complexity of the data environment. So what does it take to get the complete pipeline observability that automated data lineage can provide? 

“Take a deeper dive into the key benefits, must-have capabilities, and common pitfalls of data lineage solutions with our  “Data Lineage for DataOhttps://getmanta.com/library/documents/automated-data-lineage-for-dataops/?utm_medium=static&utm_source=partner&utm_campaign=masterdataps” whitepaper. You’ll learn how lineage helps cut manual processes, break data silos, and bridge the knowledge gap between business and technical users to keep your pipeline healthy and your company happy.