We are back in our Data Engineering Weekly Radio for edition #121. We will take 2 or 3 articles from each week's Data Engineering Weekly edition and go through an in-depth analysis.
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From editor #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.
Domain knowledge + discipline expertise
Distributed Data Ownership and shared Data Ownership
Data as a Product
Enablement over Handover
Impact through Exploration and Experimentation
Proactive attitude towards Data Privacy & Ethics
Here are a few highlights from the podcast
"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/
Here are a few highlights from the podcast
"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
Here are a few highlights from the podcast
"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.”
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