Analyze All the Things : Data Omniscience with Omni
Tomasz TunguzVenture Capitalist If you were forwarded this newsletter, and you'd like to receive it in the future, subscribe here. Analyze All the Things : Data Omniscience with Omni
Within data teams, a tension exists. Centralize the data analysis to ensure accuracy or enable end-users to analyze their own data directly which is faster & more direct. The pendulum between these two states started with centralization during the 2000s with BI products from Microstrategy, Cognos, BusinessObjects, & Hyperion. In 2004, Tableau emerged from the Stanford campus to deliver their application to the users. Cloud databases ushered in an opportunity to centralize that data analysis again. Looker’s modeling language, LookML, provided a way to define metrics across an organization. There’s a pendulum that swings in the world of business intelligence between control & freedom. In our Office Hours last week, Colin Zima CEO at Omni talked about this oscillation. BI in the future won’t oscillate between these two, but serve both purposes. How will this happen? Users work with their own metrics definitions. When they create a metric, the BI system can enable it to be promoted from the person, to the team, to the department, & potentially across the company - mediated by the data team. Metric promotion provides a unique form of collaboration that balances central control & end-user speed. This was a special Office Hours for two reasons. First, Omni celebrated their 2 year birthday as a company. Second, because we announced Theory’s $20m investment in the business. For more than a decade, we’ve been working with the Omni team at Looker. We share their vision for the future of business intelligence & are thrilled to continue to support them as they re-invent BI again. If you’d like to try the product, click here. We covered much more in the Office Hours including other technical advances like hybrid execution, the future of the semantic layer, permissioning, & the paradoxical increase in data teams & users with AI. The video is here & the podcast version here. |
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