Data tools: the good, the bad, and the ugly w/ Erik Bernhardsson
Nov 4, 2021
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Former Spotify and Better.com expert Erik Bernhardsson joins hosts to discuss trends in data tools, including the pros and cons of SQL, the rise of low code solutions, and the consolidation of data tools into one platform. They also explore the shift towards business logic over data shoveling and predict further industry consolidation.
Balanced data team structure involves centralization and collaboration with business teams.
Focus on solving critical business issues with simple analytics before complex AI solutions.
Prediction of continued separation between cloud providers and data platform companies like Snowflake and Databricks.
Deep dives
Hybrid Model: A Balance of Centralization and Decentralization
Eric highlights the importance of a hybrid model, combining aspects of centralization and decentralization within data teams. Centralization can create gatekeeper roles, while extreme decentralization may lead to hiring and retention challenges. A balanced approach involves central reporting structures and specialized team members who collaborate closely with business and product teams.
Focus on Business Needs: Data's Value lies in Solving Obvious Problems
Emphasizing the importance of addressing critical business issues, Eric underlines that data's real value often comes from identifying glaring shortcomings within a company's operations. Rather than complex AI solutions, the focus should initially be on descriptive analytics and uncovering straightforward yet impactful data insights.
Prediction on AI and Data Stack Integration
Eric foresees a future where companies like Snowflake and Databricks will remain separate from major cloud providers like AWS, Google, and Microsoft. This segregation is driven by the distinct strengths of cloud vendors in infrastructure management and the software expertise of companies like Snowflake and Databricks.
Challenges in Role Specialization
Eric questions the sustainability of roles like analytics engineers amidst the evolving data landscape. With a preference for generalists and a focus on common business goals, the delineation between data engineers, analysts, and new roles like analytics engineers may witness further evolution.
Promoting a Business-Centric Approach: Focus on Value Proposition
Encouraging a business-centric mindset, Eric advocates for aligning data efforts with core business objectives. By regularly assessing how data work contributes to business success, professionals can ensure their efforts drive meaningful value and impact within organizations.
New data tools drop daily, but are they worth the hype? Some launch with overinflated expectations, while others solve a problem that doesn’t really exist. On the flip side, there are tools that transform the enterprise and have the potential to change the way we do data forever. The question is, how can you tell the difference?
Special guest Erik Bernhardsson, formerly with Better.com and Spotify, joins Tim and Juan for a conversation on data tools; the good, bad and the ugly.
This episode will feature:
An overview of data tool types and who they serve
How to define “good, bad and ugly”
What’s your favorite spaghetti western movie?
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