Getting started with DataOps doesn’t need to be overly complicated if you just follow a few basic guidelines.
DataOps is a must-have for any successful data and analytics team because it is the most effective way to deliver better analytics faster. Increasingly, those companies that neglect to invest in process-driven innovation will be at a competitive disadvantage. But how do you convince other organizational stakeholders to prioritize this important investment today?
At Data Summit 2022, Chris Bergh, CEO and head chef of DataKitchen, shared how to build an internal business case and ways to collect small wins that illustrate the benefits of DataOps at your organization.
DataOps focuses on people and processes, said Bergh who explained that the only thing that matters in data analytics is that the data you provide is used. "Good analytics is adopted analytics," he emphasized.
Bergh cited data that 60% of analytics projects fail altogether and 87% of data science projects never get into production, according to Gartner.
Data errors in production are costly, said Bergh stating that most companies have way too many errors per month—79%.
And every data error is costly and reduces trust by constituents in the data. Moreover, errors divert time away other things that really need to get done and from more innovative endeavors, said Bergh. Only 22% of time is spent on innovation, 78% on errors and manual execution, according to Gartner.
In addition, 52% of data engineers said errors are a major source of burnout, according to DataKitchen and data.world data.
The solution is DataOps, said Bergh, which:
- Enables you to connect your existing pipelines quickly and seamlessly and does not require modifying them.
- Supports the testing and monitoring of your data at rest and does not require extracting the data from where it is currently stored.
- Requires minimal configuration.
- Provides rich context that enables rapid triage and alerting.
- Prevents issues from happening in the first place.
According to Bergh, by acknowledging the cost of bad data pipelines to the organization, and actually understanding the problems fully, there is the opportunity to make a case for adopting the DataOps methodology in order to improve and automate rather than patching problems by adding staff or new technology.
DataOps aligns people, process, and technology to enable lower error rates in production, faster deployment cycles, better productivity, and measurable success, he said.
Data Summit 2022 is taking place May 17 – 18 at the Hyatt Regency Boston with pre-conference workshops on May 16. Many presenters are also making their slide decks available for review.