How A Product Manager Mastered Data Product Management | Lessons from the DBT Experience
Discover how embracing dbt transformed Jen's journey in data product management and boosted her team's success!
Jen, Sr. Product Manager (PM), transitioned from Payments to Data team.
Upon arrival, Jen saw that everyone on the team was beaming with joy about their dbt models and tests. She had no clue what this dbt thing is! She felt like a fish out of water. The team wanted to adopt a product mindset and was excited to have their first PM.
Jen was amazed to see how different data deliverables are.
She was excited to face this refreshing challenge!
As a good PM, she created a list of her first tasks to set the team for success. This is what it looked like:
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Gather info and set targets for the quarter
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Learn about the use cases and various users
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Create a weekly summary for the stakeholders to look at product wins
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Understand the resource allocation gaps right now
Nim, saw her discomfort and booked some time with her to help.
He was an experienced analytics engineer who knew ins and outs of DBT. He already knew the important features Jen should focus on in her first three months. So here is what he shared with her:
#1. Use Exposures and Lineage to know your suppliers and users
DBT exposures can tell you who your end users are and who the owners of that data are.
To get a handle on all the use cases your team is working on, start with the mature dashboards, analyses, ml model, or applications consuming your data. To build a user feedback loop, you can talk to the creators of the exposures.
#2. Use dbt Docs and Slack to help your users with their use cases
One way to immerse yourself in the problem space is by talking to users and writing FAQs for them so that your team can work on what they do best.
When users (business users, app development teams) start using the output datasets and dashboards, they naturally ask questions. You can easily find the contextual meaning of the datasets in dbt docs. They are your biggest asset to guide users to self-serve data.
#3: Use Artifacts to learn about your bottlenecks and product performance
Use dbt metadata tools to manage your resources and priorities efficiently.
When creating a snapshot summary of what are solid product features vs the weaklings, look at the dbt artifacts and data platform query logs. This will help you align your resources with your prioritize to optimize for your end goal as a team. Some teams care about quality, others care about performance, and all care about uptime. Choose your levers to pull and create a plan.
Nim and others worked hard with Jen's product strategy. The results: