CIO OPINION become a bottleneck for deploying applications that require changes to data resources . in common frameworks that enable consistency and reduce friction .
To solve this challenge , organizations need to be able to automate , version-control and continuously manage their data just as they do application code .
The tools that they already use for DevOps – like the software you ’ ll find in a CI / CD pipeline – can help with this task , but only if you extend them to enable automated management of data resources in a way that is in sync with software delivery .
When you standardize your approach to data management , you can place your focus on analysis and the creation of value , because you ’ re no longer distracted by the work of having to manage data in inconsistent or ad hoc ways – just as a healthy DevOps strategy lets you manage application delivery in a repeatable , efficient manner .
4 . Data cost management
In addition , it ’ s important to establish metrics ( like the speed at which data schema are persisted and updated ) for monitoring the health of data pipelines , just as DevOps teams use metrics ( like app release velocity ) to manage software delivery pipelines . Without data pipeline metrics , you ’ ll be shooting in the dark when it comes to ensuring your data management processes effectively complement and enhance your software delivery processes .
3 . Make data management repeatable
Data management should also be similar to DevOps in the respect that data management should be grounded
Ensuring that data resources and processes deliver maximum financial value requires deep visibility into what the cost of each data product is and how that cost varies depending on factors such as how many people use the solution or which volume of
Tools alone don ’ t solve the complexities of modern data management .
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