Build a Unified Data Analytics Platform for Retail Department
Unified Data Analytics Platform
Build a Unified Data Analytics Platform for Retail Department
Challenge
The Manufacturing Company’s Retail organization needed a reliable and scalable analytics platform to process large volumes of externally sourced click-count data and deliver accurate, timely reporting. The data arrived as large CSV files from a third-party provider and required significant cleansing, merging, and validation before it could be used for analysis.
Key challenges included implementing a robust ETL process to handle data quality issues, ensuring the entire solution could be fully recreated in the event of a system failure or catastrophe, and optimizing processing performance. Initially, end-to-end data processing took between 8 and 12 hours, limiting the platform’s effectiveness for timely reporting and decision- making.
CLIENT
A Fortune 100 Manufacturing Company
LOCATION
Hillsboro, Oregon
TEAM SIZE
6-member delivery team
INDUSTRY
Technology/ Semiconductor/ Manufacturing/ Retail
Services
Logic Intelligence provided end-to-end data engineering and platform services, including ETL design and implementation, data quality validation, performance optimization, and operational resiliency planning. Services included building automated ingestion pipelines, cleansing and aggregating large datasets, and designing repeatable processes for backup, recovery, and documentation.
The team also implemented comprehensive documentation covering data fields, transformations, calculations, schemas, and operational procedures to ensure long-term maintainability. Performance tuning and optimization were applied to significantly reduce processing time while maintaining data integrity and reliability.
The team also implemented comprehensive documentation covering data fields, transformations, calculations, schemas, and operational procedures to ensure long-term maintainability. Performance tuning and optimization were applied to significantly reduce processing time while maintaining data integrity and reliability.
Solution
Logic Intelligence designed and implemented a unified data analytics platform using DBAAS and SSIS to ingest, cleanse, merge, and aggregate externally provided click-count data. The solution followed a structured processing flow that included backing up the existing database, ingesting large CSV files from shared storage, loading data into the DBAAS environment, executing stored procedures for cleansing and aggregation, archiving source files, and processing analytical cubes for reporting.
Significant optimizations were applied to the ETL and processing workflows, reducing overall execution time from up to 12 hours down to approximately three hours. The solution also emphasized disaster recovery readiness, ensuring the platform could be fully reconstructed using documented code, schemas, data backups, and processing logic.
Technologies Used
DBAAS (Database as a Service)
SSIS
SQL Server
Stored Procedures and Analytical Cubes
Enterprise Backup and Archival Processes
Business Outcomes
Logic Intelligence successfully delivered a scalable and resilient unified analytics platform for the Manufacturing Company’s Retail organization. The solution improved data quality and reliability while significantly reducing processing time, enabling faster access to insights. Large CSV files averaging 5–10 GB per load were processed efficiently, and over 1.5 years, the analytics database grew to approximately 132 GB while remaining stable and performant.
The platform provided the Manufacturing Company with a dependable foundation for retail analytics, improved operational confidence through robust backup and recovery practices, and enabled consistent, repeatable reporting from complex external data sources.