Advertisement

The ABCs of Treating Data as Product

Executive Editor at DATAVERSITY
Oct. 27, 2022
Advertisement

More Related Content

Slideshows for you(20)

Similar to The ABCs of Treating Data as Product(20)

Advertisement

More from DATAVERSITY(20)

Recently uploaded(20)

Advertisement

The ABCs of Treating Data as Product

  1. The Data Product ABCs Tim Gasper VP of Product, data.world + Co-host of Catalog & Cocktails
  2. Who am I to talk ● VP of Product at data.world (modern catalog, governance, query, and knowledge graph platform) ● Former Head of Data and Analytics offerings at CSC (now DXC Technologies) ● Rackspace (cloud data & analytics), Bitfusion (ML/AI training), Janrain (customer identity & analytics), Keepstream (social media analytics) ● 15+ years of product management and product marketing experience across software, SaaS, and AI and analytics products ● Speaker and writer on data, AI, product, and startups ● and… @timgasper /in/timgasper timgasper.com
  3. An honest, no BS data podcast. Honest, no-BS, non-salesy conversation about enterprise data management and analytics. It’s a 60-minute podcast elixir containing everything interesting about data and metadata management, DataOps, knowledge graphs, and more. 4.8 Top 2.5% of Global Podcast Listenership* *Listennotes.com
  4. CONFIDENTIAL ● https://www.dataversity.ne t/podcasts/ ● https://www.dataversity.ne t/my-career-in-data- episode-4-tim-gasper-juan- sequeda-of-data-world/ ● https://www.youtube.com /watch?v=Nu6LAEczg7U
  5. datadotworld data.world Highest adoption in the industry ● UX perfected with >1.8M users ● Data-driven UI and metadata model ● Catalog anything ● 1K+ releases a year, instant upgrades ● Federated data access in-platform 100% would recommend (last 12 months) datadotworld data.world The enterprise data catalog for the modern data stack powered by a knowledge graph
  6. datadotworld data.world 100% would recommend (last 12 months) datadotworld data.world The enterprise data catalog for the modern data stack powered by a knowledge graph
  7. Why all the Data Mesh buzz? What is the problem? Monolithic data infrastructures don’t scale socially Data is treated as an afterthought Why do we care? Centralized platforms and teams become a bottleneck for the business Data value is being left untapped
  8. datadotworld data.world Data Mesh 01 02 03 04 Domain Ownership Empower the folks that create and know the data best to manage it. Data as a Product Managing data with end users and stakeholders in mind. Federated computational governance Facilitate shared safety, interoperability, and enablement. Self-serve data infrastructure as a platform Data catalog & governance Data collection & integration Data storage & compute Data transformation & modeling Business intelligence & analytics Data observability
  9. CONFIDENTIAL Consuming data to solve the crucial business problems should be as easy as buying a product on your favorite e-commerce platform. How? Follow our ABCs! Takeaway
  10. datadotworld data.world Data Product ABCs Accountability Boundaries Contracts & Expectations Downstream Consumers Explicit Knowledge
  11. datadotworld data.world Accountability ● Who is the owner/trustee/ambassador that is responsible for the data? ● Who defines the requirements? ● Who fixes it when it breaks? ● Who is on call? ● Who is in trouble if the data is mishandled?
  12. CONFIDENTIAL STRATEGIC TEAM Who is playing what roles? The Cloud-Native Data Catalog CONSUMERS PRODUCERS Technical architect Project manager Program manager Executive Data steward Data engineer Data analyst/scientist Business decision maker datadotworld data.world The Cloud-Native Data Catalog datadotworld data.world Data product manager
  13. datadotworld data.world Boundaries ● What is the data? ● What isn’t it? ● Where will it live? ● How is it accessed? ● What are the inputs and outputs? ● How do you balance that roadmap against other organizational priorities and considerations?
  14. datadotworld data.world Contracts & Expectations ● What are the data constraints, definitions, and tests? ● What are the SLAs and SLOs? ● What are the sharing agreements, consented uses, and policies? ● What are the consented purposes? ● What is the performance and scale? ● What are the quality and maintainability details? ● What is security? Who can see it?
  15. datadotworld data.world Downstream Consumers ● Who are the current consumers? ● Who are potential consumers? ● What are the use cases that have been considered? ● What is the value? ● What is the roadmap of the data product? ● How will it evolve to provide more value for consumers over time? ● What is the user experience of the data? APIs, shape, access point?
  16. datadotworld data.world Explicit Knowledge ● What is the meaning? ● What is the schema/ontology? ● How is it related to other data products? ● Where is the documentation with examples?
  17. datadotworld data.world User Data Product Accountability ● The Product domain is responsible ● Technical Steward if something goes wrong with the data pipeline is Alice. ● Business Steward if there are questions about the meaning of the data is Bob. ● The Data Product Manager who is gathering the requirements and managing the roadmap is: Charlene. Boundaries ● This will contain data about users starting from Jan 1, 2022. Users are defined as people who has activated their account. ● This data product will live in our cloud data warehouse. Contracts & Expectations ● This data product will have a list of all the users. It will contain the unique internal id, date created, ... ● All the data should be complete, in other words, there is no reason for missing data. ● This is the definitive number of users. ● This data product is near real time. With up to a 1 hour lag. ● This can only be used for internal company purposes. If any of this data, including aggregated, needs to be shared outside of the company, the data product manager needs to be consulted. ● Data is available in our cloud data warehouse, therefore it can be accessed by SQL or through our BI tool. Downstream Consumers ● The customer success team is the main consumer of the data. The marketing and sales team can use this data for upsell and cross sell. Marketing team wants to use this for personalized offers, but that is not yet a target use case. Next year roadmap. ● Depending on requirements, more attributes about the users can be added, if they are already captured. ● The customer success team wants to interact with the data through a BI tool. Explicit Knowledge ● A user is any person who has signed up for our system starting on Jan 1, 2022 and that they have activated the account. The schema consists of … ● A user can be associated with exactly 1 email, … ● The User data product can be joined with the User Activity data product.
  18. datadotworld data.world Agile Data Governance process: iterate! datadotworld data.world The Cloud Data Catalog datadotworld data.world The Cloud-Native Data Catalog
  19. datadotworld data.world The time impact of being fast, incremental, and iterative Define policies Release Build workflows Define standards and principles Data Product 1 Evolve policies Release Build workflows Evolve standards/principles Analysis, Insight, Value Measure, Learn, Iterate Data Product 2 Evolve policies Release Build workflows Evolve standards/principles Analysis, Insight, Value Measure, Learn, Iterate Data Product 3 Evolve policies Release Build workflows Evolve standards/principles Analysis, Insight, Value Measure, Learn, Iterate Data Product 4 Evolve policies Release Build workflows Evolve standards/principles Analysis, Insight, Value Measure, Learn, Iterate datadotworld data.world The Cloud Data Catalog datadotworld data.world The Cloud-Native Data Catalog
  20. datadotworld data.world What are the metrics? ● How many of your employees are searching for data on a regular basis? ● How many of your employees are doing self service analysis with the data? ● How many data apps are being built to change the way the business runs? ● What are the adoption rates of your data catalog, self service analytics and BI tools? ● What are the most common types of data that employees are using to deliver business impact? ● Do you have a data community and how many people are active in it?
  21. datadotworld data.world Takeaways Consuming data to solve the crucial business problems should be as easy as buying a product on your favorite e- commerce platform. Focus on Accountability, Boundaries, Contracts & Expectations, Downstream Consumers, and Explicit Knowledge. Leverage the best practices of agile software development to create and manage your data products.
  22. Learn more about data mesh governance What’s inside? How to… ● Establish a framework for treating data as a product ● Find the right balance of decentralization and centralization ● Transform data into knowledge Download it here: data.world/resources/reports-and-tools/data-mesh-governance-white-paper datadotworld data.world The Cloud Data Catalog datadotworld data.world
  23. An honest, no BS data podcast. Honest, no-BS, non-salesy conversation about enterprise data management and analytics. It’s a 60-minute podcast elixir containing everything interesting about data and metadata management, DataOps, knowledge graphs, and more. 4.8 Top 2.5% of Global Podcast Listenership* *Listennotes.com
Advertisement