Data Transformers Podcast
Data Ops should be part of everyone on the Data team – Christopher Bergh
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Episode Title : Data Ops should be part of everyone on the Data team – Christopher Bergh
Episode Summary:
Data Ops is about working with everyone who deals with Data to deploy data related projects together. It is not just one person’s job. Christopher Bergh, CEO of Data Kitchen has embarked on Data Ops journey much earlier than the industry was asking for it. Nowadays, everybody including Gartner is talking about Ops, Data Ops, Dev Ops, ML Ops, X-ops etc. But Ops should not be a single person’s job. It should be 10% of every team member’s job to think about Operations. Just like Deming prescribed in a manufacturing process, it should be part of the system and framework.
01:35: What is Data Ops? It is about making data related folks (engineers, scientists etc.) work together to deploy the projects
03:00: Difference between Dev Ops and Data ops. They are similar in concept with Dev ops focusing on applications and Data Ops focusing on analytics. The profound difference is in the scale of teams involved.
08:37: X-ops. Gartner is focusing on X-ops with Model Ops, Data Ops, Dev Ops etc. All these concepts are about working with the system as opposed to working on individual parts. Deming philosophy.
13:00: Companies put processes like checklist meetings, stage-gates so they don’t have major issues. Once issues are found, people work all hours to fix them. Instead , we should have a system in place to fix production issues in production. Also, we should have a system to see issues before customer sees them.
18:49: Need for building a system and framework is very important. Instead of just asking a lowly paid release engineer, all the team members should be responsible for Ops.
20:59 (Headliner): Formed a Quality circle and entered each error in a spreadsheet. Love your errors. After 6 months, it got better.
26:00: Data scientists are dissatisfied because they are unable to make a business impact. Looking for perfection is not the best strategy.
Resources mentioned in this episode:
Podcast website: https://DataTransformersPodcast.Com
Chris Bergh: https://www.linkedin.com/in/chrisbergh/
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