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Where did we come from? Exploring the explosion of interest in data and data tooling

May 11, 2024 - venturebeat.com
The article discusses the evolution of data tooling and infrastructure over the past decade, highlighting the shift from the "big data" era to the "modern data stack" era, and now to the emerging "AI stack" era. The author, Pete Soderling, reflects on the lessons learned from the past, including the challenges of generating insights from big data and the complexities and costs associated with managing multiple data tools. He notes the continued growth of the data tooling landscape, driven by the boom in interest in AI, and the emergence of new challenges and opportunities associated with AI models.

Soderling suggests ways to avoid past mistakes as we enter the new "AI era". He advises enterprises to develop clarity around the specific value they expect from data or AI tools and to focus on deploying tools that can demonstrate clear value and actual ROI. He also encourages founders to avoid building "me too" data and AI tools and to consider their unique insights and experience. Lastly, he advises investors to think carefully about where value will accrue in the data and AI tooling stack before investing in early-stage companies.

Key takeaways:

  • The data tooling and infrastructure world has seen a significant increase in the past decade, with the number of companies selling data infrastructure tools and products increasing from 139 in 2012 to 2,011 in 2024.
  • The rise of AI has led to a new wave of data tooling companies, despite the lack of market consolidation from the previous wave.
  • As we enter the new "AI era", it's important for enterprises to develop clarity around the specific value they expect a particular data or AI tool to give to their business.
  • Founders and investors are advised to think carefully about the value and differentiation of the data and AI tools they are building or investing in, to avoid crowding the market with undifferentiated tools.
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