Every company is looking for the next big thing when it comes to gathering, using, and/or manipulating data. Data-driven transformation is often considered the hill upon which businesses may die in this world of ever faster changes. The search can be for the next big application, the next technological innovation, or the next procedural paradigm shift. For the latter, many are heralding DataOps as the next big thing.
According to Gartner, DataOps “applies the traditional DevOps concepts of agility, continuous integration and deployment, and end-user feedback to data and analytics efforts.” However, it goes on to clarify that it isn’t simply a technical competency, but rather a “lever for organizational change, to steer behavior and enable agility.”
Regardless of how it is defined, DataOps has captured the attention of the marketplace to the point that many technologies talk about it, yet their scope is limited to the product they hope to sell. It is important to note that even while a product such as Fuusion might assist with DataOps, DataOps is a set of practices, not a technology, and no product currently offers DataOps in a box.
Many simplify DataOps as applying Devops principles to data workflows. The idea behind this simplification is that with data workflows becoming increasingly cloud-native, the similarities in the relationship between data engineers and operations and that of dev and ops have become more and more apparent. A data product must be monitored, patched, and updated, just like a software product.
DataOps is more than this, however. Similarities in relationships aside, it is more than simply bringing operations and data engineering together, or simply managing the flow of data, but “also about ensuring everyone involved knows why the data workload is running and what the desired business outcome is.” To be successful, it must be supported not just by the data engineers, their tools, and their processes, but also by connecting with those who will actually use the data, and those who can define the business needs behind the data generated.
This distinction is important to understand, especially if selling a tool to assist with DataOps. Claims that any tool delivers DataOps are hollow at best. The best one can offer is flexibility and the ability to deliver the data where needed. Defining these needs and implementing the workflows is the province of the client, who in turn needs to recognize that simply purchasing additional technologies, or speeding up the flow of data is not enough.
As Ted Friedman of Gartner puts it , “Rather than simply throwing data over the virtual wall, where it becomes someone else’s problem, the development of data pipelines and products becomes a collaborative exercise with a shared understanding of the value proposition.”
It is in the value proposition that you will find success for your organizational DataOps efforts. Without defining what you want your data to do for you, simply having more of it faster will not net you the results promised by they hype behind DataOps. So, before contacting a vendor like us, Buurst recommends a bit of due diligence. With Fuusion, as an example, we most certainly can aid you in defining your workflows. We can get you the data you need in formats that are inherently more usable, and ensure its accuracy via provenance tracking. What we cannot do is define your goals for you, or decide what your needs are.
So what do you need? Where will your data processes benefit most from a little added speed or automation?
Is it a Utility value proposition?
This means you wish to treat your data as a utility, removing silos, and reducing manual efforts when accessing and managing data. This approach makes data available to multiple relevant roles.
Is it a business enabler value proposition?
If so, then data and analytics are focused on specific use cases, such as analysis of supply chain optimization, or fraud detection. DataOps collaboration with business unit stakeholders is key in this scenario.
Or maybe it’s a data and analytics driver value proposition?
Do you need the data and analytics to help create new products or services? Break into a new market? Generate a new revenue stream?
Quite likely, it may be a combination of any or all of these. But identifying an initial focus will certainly improve your chances of success. Applying processes or tools without considering the endgame will ensure that the full benefits of DataOps processes cannot be realized. But if you know what you need, or want help in determining those needs, Buurst is ready and willing to assist.
For more information on Buurst, DataOps and Fuusion: