Mindblown: a blog about philosophy.
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The Missing Step in Data Strategy
A data strategy usually follows a familiar path. First the company collects data. Then it cleans and governs it. The data becomes easier to find and trust. Tools turn it into reports and analysis. AI now promises to make that last part faster. Each step prepares the data for use. Then the path stops. The…
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Your Data Strategy Ends Too Early
Most data strategies have a clear end point. They define how data will be collected. They set rules for quality and access. They choose the tools that will store and analyze it. More recent versions add AI use cases and a list of work to automate. Then the analysis reaches the business and the strategy…
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AI Gives Us More Analysis. Now What?
The easiest promise to make about AI in analytics is speed. AI can write queries and summarize results. It can prepare reports and answer follow-up questions. Work that once waited in a queue can happen during a meeting. This is real progress. It is also an incomplete data strategy. More analysis does not mean a…
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The Role of Product Analytics Is About to Change
For many organizations, Product Analytics still means something fairly specific. You have a website or an app. You track what people do on it. You measure conversion, engagement, retention, feature usage, funnels and drop-off. You give product managers the data they need to decide what to build next. That model made sense when the product…
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