Retail: Data Warehousing & Business Intelligence for Warehouses
Services: Data Engineering & Reporting, Data Governance & Protection
Business Functions: IT & Ops
Technology: Power BI, Azure SQL DB, Azure Data Factory, Azure Data Bricks
Our client operated multiple IT systems in different regions around the world.
Each using different platforms, technologies and protocols. Despite having some elements of business intelligence (BI) and reporting, there was no unified BI solution for the entire enterprise. This fragmented approach led to limited reporting capabilities, which were often manual and inefficient.
The client needed a comprehensive BI solution to unify and translate data from these disparate systems, enabling better decision-making and strategic planning. Using the Azure suite of tools, we enabled our client to consolidate data, streamline reporting and make data-driven decisions.
Challenge
Multiple IT Systems
Numerous IT systems across various global regions were operated, each using different platforms, technologies, standards and protocols.
Limited Reporting Capabilities
Reporting and BI capabilities were manual and labor-intensive hindering efficient data analysis and decision-making.
Lack of Unified BI Solution
There was no single enterprise-wide BI solution, despite having some business intelligence and reporting elements, which led to fragmented data management.
Need for Strategic Insights
A comprehensive BI solution was required to unify data and provide insights for future business strategy planning.
Solution
Data Centralization
All data was loaded into Azure Data Lake Gen2 creating a centralized repository which could handle vast amounts of structured and unstructured data.
Metadata Management
Azure Data Catalog was deployed to store metadata which provided a centralized hub for data source discovery. This facilitated the ease of understanding, access and the consumption of data across the organization.
Master Data Management
Azure Virtual Machines (VMS) with Master Data services were used to provide support in managing a master set of organizational data. This structure allowed for the organization of data into models, the creation of rules for data updates and the setting of data update privileges.
Enterprise-Grade BI Models
Azure Analysis Services was used to create enterprise-grade data models in the cloud. This solution allowed advanced data mashups, modeling and the ability to secure data in a trusted tabular semantic data model.
Results
Unified Data Source
The implementation of Azure DWH provided a single source of truth for the entire system eliminating data silos and ensuring consistent data across the organization.
Advanced Data Modeling
Through the use of Azure Analysis Services, data could now be combined from multiple sources, define key metrics and secure sensitive information all within a single, trusted data model.
Improved BI and Reporting
Bi and reporting capabilities were significantly enhanced using the new system enabling more efficient and accurate decision making as well as strategic planning.
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