Using DataOps to Harness Your Data Assets

Data. We have a ton of it, these days. In fact, we generate more of it than ever, which can be both a blessing and a curse. Managing the scale is key challenge. But it is possible to effectively manage while expanding your data value. It takes a blend of organizational & technical tools, policies and practices enhanced by automation and integrated solutions.

That doesn’t mean that every business is finding this easy. Every firm is at a different stage of its data journey. Hitachi Vantara recently invited a group of CIOs from a range of different sectors to discuss their approach to data, particular in their methodology of using DataOps to harness their data assets. The roundtable event laid bare a plethora of pain points, challenges and hopes for deeper collaboration across the business, driven by the insights it’s able to uncover.

Bringing it all together

DataOps is borne out of a need to bring data functions and practitioners under single strategy. The problem is the amount of siloed technologies and teams. Tech leaders have to deal with different technologies, and convey the same information over and over again. Plus, they aren’t able to tie all the data together and make sense of it in a coordinated way. The solution starts with using technologies that serve the needs of data management, data government and analytics. There has to be a thread of metadata that’s informing all three.

There are various factors that can prevent this from happening. One attendee at the event spoke about the lack of business strategy. For instance, one part of the business, say HR, might want to generate and store data but because it’s siloed, it isn’t incorporated in a way that the business can use it strategically. In the example of HR data, it’s important for that individual team and the board to know how many people work for them. But when that data is better coordinated, the wider business can see what capacity and capabilities it has, which in turn can inform hiring strategies but also product development. There are so many ways that data can make a business more innovative if there’s a strategy around data, not just a desire to have more numbers to crunch.

Another attendee said they had the strategy but didn’t have the tools. Each team had different tools that were proprietary and didn’t talk to each other. And if the aim is to get a broader understanding of the data you have in order to use it strategically, this type of data infrastructure isn’t conducive to achieving that goal.

Two key points came forward in addressing these challenges. Firstly, it’s metadata to the rescue again. It’s imperative the business divisions can easily use their own data to do their day jobs. But the entire business needs the data about the data they have. They need for the data to interface with other datasets, wherever it resides within the business.

This is related to the other key point – the issue of flexibility. When a data estate is made up of composable parts that work well together, without forcing businesses to use everything from one provider, it gives them the breathing space they need to create a solution that works for them and the business objectives they have.

Find the purpose

It’s getting really easy to store data now. Maybe too easy. As a result, many businesses are becoming data hoarders. This was an issue that was flagged by speakers at the roundtable event. Without having a purpose for collecting the information in the first place, it’s in danger of being just vanity data that lives on spreadsheets. It serves only to make businesses feel smug about how much data they can produce.

The alternative is having data that produces tangible outcomes. The data needs to be tied to some sort of measurable improvement or efficiency, and those outcomes have to be decided from the outset. The data and tech leads should go to the business and start with the business case, build targets and track against them. What do you want to do and by when? With that approach, you know what you’re working towards, and you can make tweaks based on the initial data you’re seeing.

This approach is an important way to address a common complaint that CIOs have; that business leaders don’t fully buy into the data tools being presented to them. The truth is that business leaders don’t buy into data tools, they buy into insights that help them to improve their business. When they see this from the beginning, and see a clear roadmap to making improvements, it’s a much easier sell.

Keep it simple

DataOps is a powerful way to having a deeper understanding of the business, how it works and where the opportunities lie. But it should produce outputs and outcomes that are simple to understand, rather than adding more tools that increase complexity. Part of this is simplifying the data estate. Some businesses struggle because they have too many tools that compete to do the same thing. They’re double counting data and needlessly paying for tools that tread on the toes of other very similar solutions.

A helpful step to take with DataOps is to understand that there’s power in the collaborative big picture view of data that extends far beyond individual teams. The correlated value of data is huge, and as such businesses should look to free it up for everyone to use and benefit from. Data is at its best when its unlocked and used to its full potential, rather than locked up behind internal walled gardens, proprietary tools and minimal strategy. When used correctly, it can inform business decisions and help them to put a greater reliance on irrefutable stats and insights.