Retail Chain AnalyticsA SaaS based BI Solution for Retail Chain Owners to empower their business functions.
Problem Statement
The client is a retail sales giant having numerous stores across the USA, with each sending sales, invoice, inventory and other details in different formats. They were facing tremendous challenges like:
- Existing ETLs were unable to merge all data sources like SQL Server, Oracle, Excel, CSV, and text files together.
- Manual processing consumed significant time and effort.
- Business exceptions were causing errors in dashboards.
- Data past 2 years led to reports timing out.
- Existing ERP system couldn’t maintain historical data or automate reporting.
Solution Design & Implementation
- ETL and Data Integration
- Unified heterogeneous data from SQL Server, Oracle, Excel, CSV, and text files into a SQL Server staging database.
- Performed data cleansing and validation, routing invalid records to a separate database for correction.
- Data Warehouse Design
- Built a robust SQL Server data warehouse to store 7+ years of historical data.
- Applied business rules and transformations for analytics-ready data.
- Advanced Analytics
- Designed a multi-dimensional SSAS database with optimized MDX queries to support complex aggregations and fast data retrieval.
- Reporting and Dashboards
- Created intuitive dashboards and reports using SQL Server Reporting Services (SSRS) for granular and high-level insights.
- Embedded MDX queries within reports for efficient data aggregation.
- Automation and Process Optimization
- Automated data merging and exception handling, eliminating manual processes.
- Implemented a centralized data repository for secure, organization-wide data access.
- Security and Validation
- Enforced a strong security framework for access control across raw data, processed data, and final reports.
- Improved data integrity by automating validation and exception management.
Results
Here’s what we achieved with the new system:
- 25% Time saved of operation teams due to the automation of data ingestion, cleansing, and reporting.
- 80% reduction in data issues due to improved data accuracy and integrity through automated validation and exception management.
- 7+ Years of Historical Data available to query for business users.
- Legacy ETLs tuned to run 60% faster to save time and resources on the server.
- Server Idle Time increased by 16% post performance tuning to make it available for ad-hoc processes and better scheduling.
- 90% Lesser Server Incidents reported post optimizations and tuning.
- Data Integration of 10+ Data Sources done and loaded to DW for comprehensive reporting.
