Teams that rely on data pulled from a number of different sources need to be able to collaborate in a way that is not hampered or hobbled by this potential for fragmentation.
This is where DataOps can come to the rescue, providing a way to combine the various threads of disparate data sources and organize them according to metadata and dependencies. This not only has moment-to-moment benefits for the people tasked with interpreting and acting upon the data in question, but also allows you to glean value from the overarching view of your data ecosystem and the lifecycle of information passing through your business.
Failing to make use of collaborative practices which integrate elements of DataOps strategy will limit the productivity of teams and create bottlenecks at various points in the pipeline.
Automation ensures consistent performance
Another aspect of DataOps which provides perks to those looking to update their collaborative practices is that it introduces elements of automation to collecting, integrating and leveraging data.
It is worth noting that to achieve the ideal levels of process automation further down the line, it is necessary to put in the hard work of planning and testing appropriately up front. However, once a framework is put in place that has been tried, tested and approved by various team members, the wheels of collaboration will be thoroughly greased for good.
This is especially useful when new people join a team, as the practices which are already established will make it simpler for them to adapt to their new roles, and not force them to wrangle with tedious processes which are being handled through a degree of automation.
Like DevOps, DataOps is ideally suited to ensuring that collaboration is not only handled effectively within specific teams, but also across different departments within an organization.
It accepts the likelihood that not every individual will have the same background and level of experience, and so in order to collaborate on a level playing field it is necessary for policies and practices to account for this discrepancy.
Eventually this should ensure that everyone is pulling in the same direction, with the use of a variety of tools and solutions being mutually beneficial as they move towards the shared goals of the business.While the creation and implementation of DataOps-based collaborative practices will not happen overnight, it is a process which can provide perpetual benefits in the long run, and so should be sought out by any small business that is eager not to get left behind as data growth accelerates.