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From Data Engineering Weekly Edition #121, we took the following articles

Oda: Data as a product at Oda

Oda writes an exciting blog about “Data as a Product,” describing why we must treat data as a product, dashboard as a product, and the ownership model for data products.

https://medium.com/oda-product-tech/data-as-a-product-at-oda-fda97695e820

The blog highlights six key principles of the value creation of data.

1. Domain knowledge + discipline expertise


2. Distributed Data Ownership and shared Data Ownership


3. Data as a Product


4. Enablement over Handover


5. Impact through Exploration and Experimentation


6. Proactive attitude towards Data Privacy & Ethics

https://medium.com/oda-product-tech/the-six-principles-for-how-we-run-data-insight-at-oda-ba7185b5af39

Ashwin & Ananth Conversation Highlights

• "Oda builds the whole data product principle & the implementation structure being built on top of the core values, instead of reflecting any industry jargons.”

• "Don't make me think. The moment you make your users think, you lose your value proposition as a platform or a product.”

• "The platform enables the domain; domain enables your consumer. It's a chain of value creation going on top and like simplifying everyone's life, accessing data, making informed decisions.”

• "I think putting that, documenting it, even at the start of it, I think that's where the equations start proving themselves. And that's essentially what product thinking is all about.”

Peter Bruins: Some reflections on talking with Data leaders

Data Mesh/ Data Product/ Data Contract all the concepts trying to address this problem, and this is a Billion $ $ $ worth of a problem to solve. The author leaves a bigger question, Ownership plays a central role in all these concepts, but what is the incentive to bring Ownership?

https://www.linkedin.com/pulse/some-reflections-talking-data-leaders-peter-bruins/

Ashwin & Ananth Conversation Highlights

• "Ownership. It's all about the ownership." - Peter Burns.

• "The weight of the success (growth of adoption) of the data leads to its failure.

Faire: The great migration from Redshift to Snowflake

Is Redshift dying? I’m seeing an increasing pattern of people migrating from Redshift to Snowflake or Lakehouse. Flair wrote a detailed blog on the reasoning behind Redshift to Snowflake migration, its journey, and its key takeaway.

https://craft.faire.com/the-great-migration-from-redshift-to-snowflake-173c1fb59a52

Flair also opensource some of the utility scripts to make your life easier to move from Redshift to Snowflake

https://github.com/Faire/snowflake-migration

Ashwin & Ananth Conversation Highlights

• "If you left like one percent of my data is still in Redshift and 99% of your data in Snowflake, you're degrading your velocity and the quality of your delivery.”

We thank all the writes of the blog for sharing their knowledge with the data community