Case Study
Building a Self-Service Data Platform for Business Users
Problem Statement
A multinational insurance company relied heavily on its IT and data engineering teams to generate reports and run analytics. This created delays in business decision-making, overloaded technical teams, and led to data bottlenecks. The organization needed a self-service data platform that would empower non-technical business users to access, explore, and visualize data securely—without writing code or relying on IT support.
Challenge
Dependence on Technical Teams: Business analysts couldn’t independently access or query data.
Data Silos: Critical data was fragmented across departments and systems (CRM, ERP, spreadsheets, etc.).
Security & Governance: Ensuring that self-service access didn’t compromise sensitive data.
User Experience: Creating an interface that was intuitive for non-technical users, yet powerful enough for deep insights.
Solution Provided
The company built a cloud-based self-service data platform integrating multiple data sources into a unified environment with governance controls and user-friendly analytics tools. Key features included:
Data Lakehouse Architecture: Unified structured and unstructured data into a central, queryable format.
Role-Based Access Controls: Ensured that users only accessed data relevant to their roles or departments.
Drag-and-Drop BI Tools: Integrated Power BI and Looker for self-serve dashboards and visualizations.
Data Catalog & Search: Implemented a metadata-driven catalog for data discovery and understanding.
ETL Automation: Used tools like Apache Airflow and dbt to schedule and clean incoming data feeds automatically.
Development Steps
Data Collection
Conducted workshops across sales, marketing, finance, and operations to identify reporting gaps and expectations.
Platform Architecture Design
Designed a scalable architecture on Azure with a central data lake, BI tool integration, and access layer.
Data Integration
Connected CRM (Salesforce), ERP, spreadsheets, and cloud databases into a unified platform.
Security & Governance Layer
Defined access rules using Azure Active Directory and implemented data masking for PII.
Training & Onboarding
Created onboarding tutorials, conducted user training, and offered live Q&A sessions for adoption.
Monitoring & Feedback
Collected user behavior analytics and monthly feedback to improve UX and address adoption challenges.
Results
Report Generation Time Reduced by 85%
Business teams generated insights in minutes, instead of waiting days for IT support.
Adoption by 70% of Business Teams
In the first quarter post-launch, 70% of eligible users created dashboards or queried data at least once weekly.
IT Ticket Volume Reduced by 60%
Fewer reporting and data access requests freed up IT for higher-priority technical work.
Faster Decision-Making Across Departments
Marketing campaigns, budget planning, and customer support decisions became more data-informed and timely.
High Data Security & Auditability
All access was tracked, with clear lineage and full compliance with internal and external governance standards.