Problem
The client was manually pulling Google Analytics and Salesforce data into spreadsheets every reporting cycle, which meant decisions were always made on data that was already a week or a month old by the time anyone looked at it.
Turning Weekly Spreadsheet Reporting Into a Daily Analytics Pipeline
Case studyContext & Data
The client needed ongoing visibility into business performance, not just a periodic snapshot — and the manual process behind the existing spreadsheets couldn't keep up with that cadence.
Approach
I built a Python pipeline that pulled Google Analytics data daily through its API, alongside the client's Salesforce data, then separated the work into distinct extraction, cleaning, and storage stages so each could be maintained independently — landing the processed data in BigQuery before it fed a set of Power BI dashboards built for executives to check on their own, without needing to touch the underlying data.
Tools
Python for the pipeline, the Google Analytics API for extraction, BigQuery for storage, and Power BI for the dashboards themselves.
Analysis & Execution
Beyond building the initial pipeline and dashboards, I maintained and optimized them on an ongoing basis, working directly with the client's stakeholders to understand what they actually needed to make decisions rather than just handing off a fixed set of reports.
Result
Reporting moved from a weekly-or-monthly view to a daily one, giving the client's stakeholders current information instead of a stale snapshot.
Learnings
Working closely with stakeholders to understand what they actually needed mattered more than the pipeline itself — the goal was aligning deliverables to real business needs, not producing dashboards or reports for their own sake.