Digital Transformation and Cloud-Based Unified Data Analytics Platform
Digital Transformation
CLIENT
A Fortune 100 Manufacturing Company
LOCATION
Hillsboro, Oregon
TEAM SIZE
2 Teams with 8-member s delivery team
INDUSTRY
Technology, Semiconductor, Manufacturing
Challenge
The Manufacturing Company’s Worldwide Sales and Marketing and IT organizations needed to align globally distributed teams to a single source of truth so teams could analyze data consistently, reduce duplication, and create a centralized place for insights.
Key challenges included establishing enterprise data governance, improving data quality and consistency across many datasets, enforcing security for sensitive data at scale, and providing a standardized reporting experience that still allowed advanced users to create their own insights without creating new silos
Services
Logic Intelligence provided end to end services spanning architecture, data governance, data engineering, reporting, and platform operations. Services included solution architecture design on Azure, defining a data stewardship operating model, implementing data quality monitors and cleansing standards, and building a centralized data dictionary to document dataset definitions, sources, rules, and calculations.
Logic Intelligence also implemented security controls using entitlement groups and row-level restrictions, developed reporting templates and a consistent Power BI experience for broad adoption, enabled enterprise release practices using CI CD across environments, and implemented resiliency practices such as backup and restore strategies to minimize end-user impact during data issues or platform changes
Solution
Logic Intelligence delivered a cloud-based unified data analytics platform designed to support very large-scale data and global usage. The architecture landed data into Azure storage, processed data with Databricks, and published curated data products through Azure Synapse Analytics for governed consumption and reporting. Power BI apps provided standardized dashboards and shared datasets, so end users could consume trusted insights and super users could extend reporting without duplicating data.
To prevent teams from going rogue with specialized datasets, the solution also supported controlled updates for certain custom or specialized data through master data management capabilities, bringing those updates back into the governed platform and keeping relationships and definitions consistent.
Technologies Used
Core Cloud Data Platform
Microsoft Azure, Azure Storage and Blob Storage, Azure Synapse Analytics, Azure Data Factory, Microsoft Fabric
Data Processing and Lakehouse
Databricks, Delta Lake
Data Warehouse and Data Estate Integrations
Snowflake, SQL Server, Teradata, Cloudera, Denodo
Business Applications and Sources
Salesforce, Excel
Governance, Metadata, and Master Data
Collibra, Profisee
Reporting and Automation
Power BI, Power Automate, Tableau
DevOps and Version Control
GitHub, Azure DevOps, Databricks CI CD, Power BI CI CD pipelines
Business Outcomes
The Manufacturing Company gained a unified platform that enables global teams to access, analyze, and report using consistently governed datasets, improving clarity across organizations while reducing duplicated data and duplicated effort.
The program established repeatable governance practices through named data stewardship ownership, documented definitions through a centralized data dictionary, and ongoing data quality monitoring to increase trust in analytics outputs.
Security and access controls were implemented to support appropriate access by role and region, enabling broader self-service analytics while protecting sensitive data. Standardized reporting through Power BI apps and managed release pipelines improved consistency, reliability, and operational supportability across environments.