Cutting through the noise of data products — Pedram Navid // Dagster Labs
Pedram Navid
Dagster Labs
- Part 1 Cutting through the noise of data products — Pedram Navid // Dagster Labs
- Part 2The role of AI and LLMs in data — Pedram Navid // Dagster Labs
Show Notes
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01:47The data product movementThe data product movement addresses the historical challenge of data teams wanting to move beyond fulfilling tickets. By applying product management best practices to data work, teams can deliver high-quality data products to stakeholders, enabling self-serve capabilities.
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04:17Navigating the transition to data productsTransitioning to data products requires training to shift stakeholders' approach to data. Data teams need to figure out how to productize their work and bring stakeholders along on the journey, emphasizing that a partnership is required for success.
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05:21Bringing stakeholders on board with a data products approachTo get stakeholders on board, conduct sit-down sessions and explain the larger goal. Emphasize the mutual benefits: data teams work on more impactful projects, and stakeholders gain access to higher-quality products, enabling quicker insights into their business activities.
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06:30Thinking like a product manager when creating data productsWhile dashboards are a common starting point, the key is turning processes into products. Think like a product manager, enhancing outputs by incorporating things like feedback mechanisms to ensure organizational impact.
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07:49Empowering data teams with product management responsibilitiesEquipping a data team for PM responsibilities can include members taking on the role for career growth. Alternatively, some teams opt to incorporate dedicated PMs with skills in prioritization, stakeholder communication, and outlining strategic roadmaps for the data team.
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08:35Trade offs between building data products and addressing ad hoc requestsOrganizations will have to overcome the friction of transitioning from an established process to data products. However, this transition will force stakeholders to carefully consider their data requests and how they will use the data to make strategic business decisions.
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11:05The rise of self service data cultureWith increasing data literacy across the organization, leaders across all business lines want access to data without needing to rely on someone. Building compelling and easy-to-use data products encourages stakeholders to quickly embrace and utilize these tools.
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12:48The impact of data products and data teams on organizational connectionsData teams ensure every team is empowered to answer questions on their own. Secondly, they serve as a neutral check to ensure no team has too much influence over data calculations, promoting a healthy balance between business leader perspectives and what's best for the organization.
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14:43Getting started in thinking about data as a productThe "Locally Optimistic" Slack community provides valuable resources and discussions on the topic. Secure buy-in from stakeholders by demonstrating how it will benefit the organization and reach out to the data community for support when faced with organizational challenges.
Quotes
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"There will always be stakeholder requests, but if we start to think about data as a product itself for the other 80% of the time, we can focus more on building data products that people can consume and use." - Pedram Navid
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"If you start to build data products that are compelling and easy to use, stakeholders will tend to gravitate towards that very quickly." - Pedram Navid
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"Everyone is a data person at most organizations these days. From marketing to sales SEO, leaders in these lines of businesses are data literate, want access to data, and don't want to rely on someone else to get that data." - Pedram Navid
- Part 1 Cutting through the noise of data products — Pedram Navid // Dagster Labs
- Part 2The role of AI and LLMs in data — Pedram Navid // Dagster Labs
Up Next:
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Part 1Cutting through the noise of data products — Pedram Navid // Dagster Labs
Pedram Navid, Head of Data Engineering and DevRel at Dagster Labs, explores data products and AI and large language models’ roles in data. With the rising data literacy levels in organizations, leaders are increasingly inclined to access data independently. Shifting towards viewing data as a product, data teams can strategically enable self-service and empower them to find the answers they need to make business decisions. Today, Pedram discusses cutting through the noise of data products.
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Part 2The role of AI and LLMs in data — Pedram Navid // Dagster Labs
Pedram Navid, Head of Data Engineering and DevRel at Dagster Labs, explores data products and AI and large language models’ roles in data. While AI has limitations, it offers data practitioners new ways to explore and leverage data, transforming the analysis process. Further, AI and LLMs democratize access to data analysis for non-technical people, enabling them to explore and derive insights from complex datasets without feeling overwhelmed. Today, Pedram discusses the role of AI and large language models in data.
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