Going Deeper Into Data Platform Product Management
Welcome to a deeper dive into Platform Product Management. Specifically, data platform product management.
What is data platform product management? Why is it different from traditional product management? Or is it?
This is a series of blog posts that I have been meaning to write for quite some time, and now that I have gotten over my procrastination, here we go!
Here is the entire series:
Data platform product manager’s close partners
Putting it together and becoming an effective data platform product manager
You may be wondering why you should be reading what I have to say. Let me start with a brief introduction.
I have worked in the world of data, analytics, business intelligence and insights for over two decades at big companies and small, and across a wide variety of industries and applications. I started as an ETL developer and moved to project management and program management before settling into my true passion which is product management.
My product management journey includes:
- Zero to one data products like a home-grown data catalog which covered 100% of the data footprint, cataloging over 2 million objects across almost a dozen technologies
- Exploding growth of existing data products like Jupyter-based notebooks platform for over 4,500 data scientists, data analysts and engineers starting at around 100 beta users and getting it to 1,500 monthly active users
- Creating products in the complex world of data infrastructure like an application lifecycle management product which helped engineers write SQL, Scala, Java and Python applications including components like application registry, templatized source code repository, CI and CD, orchestration/scheduling and of course standard observability
- Moving a two-decade old data infrastructure footprint to public cloud
- Numerous internal and external talks and posts (some of which are linked above)
- Some approved patents around the technologies implemented above
In all these experiences and products, the one thing that has been true is that 99% of the time, my products were consumed by customers internal to the company.
This brings me to the definition of a “data platform product manager”, at least for the purpose of this blog post series.
I see a data platform product manager as someone who creates products on top of the core data platforms like on-premises databases like Oracle or Teradata, and cloud services like Google BigQuery or Snowflake, etc. The products they create have features to simplify, standardize, stay compliant with internal and external policies, and in general to abstract away the infrastructure complexity from the users.
Note: I believe a lot of what I am going to write can potentially be applied to core infrastructure platform product management too, but I will focus on data platforms since that is where I have worked for a long time.
The intended outcomes of this series are broadly:
- To share my perspective in this area, on which I have not found much information elsewhere, probably because this type of a role is relatively new
- To invite explicit feedback — the good, the bad and the ugly — from other platform product managers who want to collaborate on how to define and refine our reason to exist and how to communicate the value we add to an organization
- To guide new product managers and provide a set of expectations for them to succeed in their role if they take on data platform product management
- To offer some insights to data platform product management leaders on what it takes to succeed as a leader in this area
Next in the series: who are the data platform products’ customers?
Then: what should be your products’ goals and typical North Stars?
If you have questions or comments, please feel free to reach me at romit dot mehta at gmail or DM me on LinkedIn, besides commenting/discussing here itself.
