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BI Infrastructure & Self-Serve Dashboards (3 Months)

Turn your BI setup into a decision-making powerhouse with structured data models & self-serve dashboards.

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Our approach

Our 3-Phase Approach

BI Discovery & Roadmap
Weeks 1-3
Define the data models, dashboards, and self-serve analytics that business teams need.
BI Model Implementation & Dashboard Buildout
Weeks 4-10
Build optimized BI models, improve data speed, and set up self-serve dashboards.
Training & Self-Serve Adoption
Weeks 11-12
Train teams to use BI tools effectively and ensure long-term success.
Phase 1
Weeks 1-3

BI Discovery & Roadmap

Goal:
Define the data models, dashboards, and self-serve analytics that business teams need.
1
Audit existing BI & reporting setup
Review data warehouse (BigQuery, Snowflake, Postgres, etc.)
Assess current dashboards (Metabase, Looker, etc.)
Identify slow queries, redundant reports, and inefficiencies
2
Stakeholder workshops to define BI needs
Interview business leaders to determine what metrics they rely on.
Identify the top 20% of questions that generate 80% of BI requests.
Understand why self-serve analytics adoption is low.
3
Define BI data model priorities
Map data sources to key metrics.
Prioritize most critical data transformations needed for dashboards.
4
Deliverables:
BI execution roadmap (clear milestones for modeling & dashboarding).
Prioritized list of data models & dashboards to be built.
Schema documentation for key data tables.
Phase 2
Weeks 4-10

BI Model Implementation & Dashboard Buildout

Goal:
Build optimized BI models, improve data speed, and set up self-serve dashboards.
1
Design & build core BI data models
Migrate 30+ key BI models from Postgres to BigQuery/Snowflake.
Optimize schema to improve query speed & reduce report lag
Implement data validation policies to maintain data integrity.
2
Set up dashboards for business & product teams
Build 5-7 Metabase/Looker dashboards for:
Product analytics (retention, feature adoption, user journeys)
Business KPIs (revenue, activation, churn, LTV analysis)
Marketing & growth insights (campaign performance, attribution)
3
Deliverables:
Optimized BI models with faster query performance.
 Self-serve dashboards covering core business & product insights.
Data validation policies to ensure long-term reliability.
Phase 3
Weeks 11-12

Training & Self-Serve Adoption

Goal:
Train teams to use BI tools effectively and ensure long-term success.
1
Train PMs, analysts & execs on BI tools (Metabase, Looker, etc.)
How to explore & filter data to answer their own questions.
How to validate insights & avoid reporting errors.
How to make better product & business decisions using data.
2
Create documentation & governance best practices
Dashboard documentation (definitions, filters, key metrics).
BI governance guide (how to prevent data drift & reporting errors).
Playbooks for self-serve analytics adoption.
3
Deliverables:
Training sessions for teams on BI tools & best practices.
Comprehensive dashboard & data governance documentation.
Finalized handoff with ongoing support options.