Clean and transformed datasets ready for analysis.
SQL queries, scripts, and logic used in the analysis.
Python notebooks or scripts for automation, modeling, or ETL.
Interactive dashboards in Power BI or Google Data Studio.
KPI definitions and performance metrics tailored to the business.
Insights report summarizing findings, patterns, and trends.
Visual presentations highlighting key insights and recommendations.
Documentation of data sources, models, and analysis steps.
Automation workflows (if required) for recurring reporting.
Final handover and walkthrough session to explain the solution.