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#154 How Can Data Marketplaces Help Realize the Most Value from Our Data - Interview with Mozhgan Tavakolifard, PhD
Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/
Please Rate and Review us on your podcast app of choice!
If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here
Episode list and links to all available episode transcripts here.
Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.
Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here. You can download their Data Mesh for Dummies e-book (info gated) here.
Mozhgan's LinkedIn: https://www.linkedin.com/in/tavakolifard/
In this episode, Scott interviewed Mozhgan Tavakolifard, Data and AI Lead for the Nordics at Accenture. To be clear, she was only representing her own views on the episode.
Before we jump in, most of the conversation was about external data marketplaces rather than internal data marketplaces within an organization. It's also important to note that data marketplace technology and implementations are still in the relatively early stages - it's quickly evolving and maturing.
Some key takeaways/thoughts from Mozhgan's point of view:
- Data marketplaces - internal and external marketplaces here - significantly lower the bar to data consumption because of standard metadata and user experiences. You should be able to easily see quality metrics, who owns a data product, access documentation, etc.
- Data marketplaces, when done right, significantly lower the time to value realization for both data producers and consumers/purchasers. And standard quality measurements and metadata make it easy for consumers to understand how much they can trust data to make purchasing decisions easier.
- Practices and tools are emerging for tracking data quality all the way to source to increase the trust data consumers/purchasers can put on data, especially for data marketplaces.
- For external data marketplaces, trust and security are still major pain points. How can data producers trust consumers will protect the data they acquire and use it legally and ethically? What is their risk to consumers behaving improperly?
- ?Controversial?: Mozhgan believes smart contracts and blockchain/distributed ledgers can provide for compliant use by...
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By Data as a Product Podcast Network
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99 ratings
Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/
Please Rate and Review us on your podcast app of choice!
If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here
Episode list and links to all available episode transcripts here.
Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.
Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here. You can download their Data Mesh for Dummies e-book (info gated) here.
Mozhgan's LinkedIn: https://www.linkedin.com/in/tavakolifard/
In this episode, Scott interviewed Mozhgan Tavakolifard, Data and AI Lead for the Nordics at Accenture. To be clear, she was only representing her own views on the episode.
Before we jump in, most of the conversation was about external data marketplaces rather than internal data marketplaces within an organization. It's also important to note that data marketplace technology and implementations are still in the relatively early stages - it's quickly evolving and maturing.
Some key takeaways/thoughts from Mozhgan's point of view:
- Data marketplaces - internal and external marketplaces here - significantly lower the bar to data consumption because of standard metadata and user experiences. You should be able to easily see quality metrics, who owns a data product, access documentation, etc.
- Data marketplaces, when done right, significantly lower the time to value realization for both data producers and consumers/purchasers. And standard quality measurements and metadata make it easy for consumers to understand how much they can trust data to make purchasing decisions easier.
- Practices and tools are emerging for tracking data quality all the way to source to increase the trust data consumers/purchasers can put on data, especially for data marketplaces.
- For external data marketplaces, trust and security are still major pain points. How can data producers trust consumers will protect the data they acquire and use it legally and ethically? What is their risk to consumers behaving improperly?
- ?Controversial?: Mozhgan believes smart contracts and blockchain/distributed ledgers can provide for compliant use by...