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Product analytics tools like Amplitude and Mixpanel are built for product teams to self-serve behavioural analysis. Data analytics tools are the broader infrastructure layer - where data from across the business gets stored, transformed, and queried. As a PM, you don’t need to build this stack, but understanding it helps you ask better questions and work better with data teams 🏗️

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The modern data stack

Data warehouse - the central store where data from multiple sources lands. Snowflake, BigQuery, and Redshift are the dominant options. Raw event data, CRM records, support tickets, billing data - it all ends up here, queryable with SQL. ETL / data pipeline tools - move data from source systems into the warehouse. Fivetran and Airbyte automate connectors to hundreds of data sources. dbt (data build tool) transforms raw data into clean, analysis-ready tables inside the warehouse. Business intelligence (BI) tools - the layer that makes warehouse data accessible without writing SQL. Looker, Tableau, Metabase, and Mode let analysts and PMs build dashboards and explore data visually. Looker’s LookML model is particularly powerful for defining metrics consistently across an organisation. Reverse ETL - sends data from the warehouse back into operational tools. Customer success teams getting churn risk scores in Salesforce, marketing teams syncing segments into their email tool. Tools like Census and Hightouch handle this 💡

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Why PMs should care

You’re probably not writing SQL every day - but you will work with data teams who do. Understanding the stack means:
  • Knowing where a metric comes from and how it’s defined
  • Being able to have an informed conversation about data quality and reliability
  • Understanding why some data requests take a day and others take a week
  • Knowing what’s possible vs. what requires significant engineering work
The gap between “I need to know X” and “the data team can tell me X” is often a communication gap rather than a capability gap 🙌

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The SQL question

Should PMs know SQL? The honest answer: even basic SQL knowledge - SELECT, WHERE, GROUP BY, JOINs - dramatically increases your analytical independence. You can answer simple questions yourself, validate numbers before presenting them, and write better data requests. It’s one of the highest-ROI skills a PM can pick up and doesn’t take long to reach a useful level of fluency. Lesson learned: the most analytically capable PMs I’ve worked with weren’t the ones with the fanciest tools - they were the ones who could write a SQL query to check their own assumptions before walking into a meeting.