From Spreadsheets to a Modern Data Stack: A Practical Migration Path

• Multiple conflicting copies of "the truth."
• Manual copy‑paste refreshes that break under pressure.
• Files too big or too slow to open.
• No reliable history of who changed what, and when.

• Centralise: load raw data into a warehouse (BigQuery, Snowflake, or Postgres).
• Model: transform with tested, documented SQL.
• Visualise: connect a BI tool for self‑serve dashboards.
• Automate: schedule refreshes and monitor them.

Start with the one report that hurts most. Prove value in weeks, then expand. The goal is fewer manual hours and numbers everyone trusts—not technology for its own sake.