DataOps & CollaborationApril 22, 2020
So, you’ve started collecting data and have amassed yourself a large pool of raw data. Now, what? In the modern world of big data, many companies have started collecting demographic and psychographic data in order to better market themselves to their target demographic. Unfortunately, while the idea is fantastic, the cruel reality is that using it to generate business value and accurate insights is much more complicated than you might think. That is why DataOps was created.
While it is not an application or physical tool, DataOps was designed to solve challenges associated with inefficiencies in accessing, preparing, integrating and making data available. In order to remedy these issues, the methodology focuses on enabling collaboration across organisations to drive agility, speed and new data initiatives.
Collaboration & DataOps
While DataOps has become high associated with automation and applications that promote automation, it is always important to remember the individuals behind the technology. DataOps, as a practice, requires deep collaboration across all functions since all parts of the process are interconnected.
As shown by the above image, sustaining DataOps within a team requires collaboration and trust of the people involved, the process and the technology used. Since all parts are so intricately connected, failure in one part could slow the entire system. This is why teams who have built their practice on the DataOps methodology place high value on teamwork, communication and project management.
The DataOps methodology has long been celebrated for its ability to help companies streamline and manage workflow in the modern every-changing business sphere. As such, more and more organisations have been adopting the practice as a means to boost themselves to reach better heights. But, despite its popularity, maintaining the dataops methodology in your team is not easy.
Collaboration is the bi-product of trust and faith amongst team members within an organisation. Both of which are impossible to groom overnight. To achieve them, project heads and managers need to put in the effort to grow and water the seeds of teamwork amongst their peers by ensuring that there is a consistent channel of communication between all team members. When changes are made to any source code or when the pipeline is triggered, fails, completed or deployed, team members need to be notified. This is so that, in the event of failure, the problem can be swiftly rectified and dealt with to ensure the product’s success and customer’s satisfaction.
In this circuit breaker where team members are no longer in close proximity, putting in those extra minutes to encourage extra minute to increase collaboration is crucial for teams to function efficiently.
To help track and improve your team’s collaboration, start using VAL’s FREE plan which allows you to store your data on a cloud-based platform. If you think you want to learn more, have a chat with ThinkVAL to learn more about how you can improve your business with the power of data.
IBM. (2019, December 18). What is DataOps? Big Data & Analytics Hub
CIO. (2017. November 21). What is DataOps? Collaborative, cross-functional analytics
IBM. (2019). Deliver businessready data fast with DataOps
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