Today, most data and analytics leaders recognize that DataOps provides the foundation for analytics excellence. Yet most struggle to get their DataOps program off the ground. This is because DataOps requires a cultural shift within an organization, including a realignment of people, processes, and technology. From his perspective leading DataOps transformations at enterprise organizations, Chris Bergh, DataKitchen's head chef and CEO, shared steps for success in an enterprise DataOps journey at Data Summit Connect 2021.
According to Bergh, many analytics and data projects today are not delivering what businesses require. They just take too long to deliver value and are too slow for the speed of business, and often, what the projects are delivering is wrong and the customer doesn’t trust it, Bergh said.
Bergh defined DataOps as a combination of technical practices, cultural norms, and architecture that enable rapid experimentation and innovation for the fastest delivery of new insights to customers, delivers low error rates, supports collaboration across complex sets of people, technology, and environments, and ultimately results in clear measurement and monitoring of results.
In this comprehensive presentation on DataOps, Bergh covered considerations such as how to get a DataOps project off the ground, example use cases, how to find a first use case, how to get buy-in at your organization, steps for evaluating progress, and pitfalls to avoid.
Keys to DataOps Transformation
Bergh cautioned attendees to beware of “big bang” approaches to change and that to have small teams working in a DataOps/Agile method first is key. Once there is demonstrable proof of success, people will see it as a benefit to their career and a way to gain new skills and help the company, he said.
It is also important not to lose sight of the “soft things” such as social proofs, pushback on change, and cultural transformation. Also, Bergh said, do not ignore the amount of staff time that needs to be focused on DataOps. And finally, be sure to measure the benefits of DataOps, he added, stressing the importance of instrumenting the production process and development process to show that you can really “have it all” with DataOps.
Gaining Support and Buy-In for DataOps
To gain executive support for DataOps, Bergh suggested a multi-pronged strategy, including the following:
Start with the problems the executive notices:
- Are the data science/engineering/analytics teams delivering the insight that business needs?
- Do business users mistrust the data itself or the team working on the data?
- Do they have a layer of consultants and shadow teams doing the work?
Map the journeys that data takes from source to value and look for problems:
- Where have there been historic issues/errors?
- Which teams own what part of the process?
- Measure how fast you can respond to errors and requests.
Look at the data science/engineering/analytic development process:
- How fast you can deploy new ideas into production.
- How long does it take to create a development environment?
- How up-to-date is the development environment?
- How well-governed is that environment if it supports self-service?
Bergh’s session was titled “The Journey to Enterprise DataOps Success.”
More information about Data Summit Connect 2021 is available here.
Replays of all Data Summit Connect 2021 sessions will be available to registered attendees for a limited time, and many presenters are making their slide decks available to attendees as well.