Analytics starts with data, not with a dashboard.

1. 01

   Audit & goals

   We look at the decisions you make, build a KPI tree and check what data you already have.

   Output:

   KPI tree, source list

   Typical time:

   3–5 days

2. 02

   Tracking

   I set up or fix data collection: GA4 events, UTM tagging, AppsFlyer, conversions.

   Output:

   Event plan, verified tracking

   Typical time:

   1–2 weeks

3. 03

   Pipelines

   I extract data from your sources (ETL) into BigQuery or PostgreSQL on a schedule, with completeness checks.

   Output:

   Automated daily loads

   Typical time:

   1–3 weeks

4. 04

   Data model

   I clean duplicates, join sources and lock metric definitions — one source of truth for everyone.

   Output:

   Metric dictionary

   Typical time:

   1–2 weeks

5. 05

   Dashboard

   I build the workspace: KPIs with notes, charts, tables, access roles, your design.

   Output:

   A working workspace

   Typical time:

   2–3 weeks

6. 06

   Automated reports

   Scheduled Telegram digests and anomaly alerts.

   Output:

   Reports and alerts

   Typical time:

   3–5 days

7. 07

   Support

   I keep an eye on data quality, add metrics and help you draw conclusions.

   Output:

   Monthly iterations

   Typical time:

   monthly

Timelines are estimates and depend on the number of sources — I’ll confirm after the audit.