Business Intelligence Workload Migration from Traditional ERP systems to Azure Data Lake

Business Intelligence Workload Migration from Traditional ERP systems to Azure Data Lake

Client Introduction & Business Requirement

Our client is one of the world’s largest manufacturers and sellers of cement roofing; they offer comprehensive building solutions focusing on fibre cement roofing sheets, ceiling products, walling material, and other Housing Industry products & services. Their critical need was to move their Business Intelligence (BI) workloads from ERP systems such as SAP , Salesforce, internal transactional systems and Excel spreadsheets into a Central Data Management Platform.

The Leadership and Business teams were in need of a standardized structure for MIS Reports, and to track their performance across their Business Units – SBUs.

Solution Overview

  • Our client was keen to standardize the structure for MIS Reports, Business KPIs and to track their performance across their Business Units – SBUs. They were also in need of implementation of new KPIs as part of their business expansion.
  • As part of Business Transformation, the existing process and measures have been incorporated into a new intuitive system consisting of Dashboards and Reports for business units across Products and Zones in Sales, Logistics, Procurement, Quality and Finance.
  • Reports have been built using principles from Dimensional modeling, which has helped the client to easily slice and dice the data in an organised manner.
  • As a part of Data Visualization, intuitive Dashboards on Power BI have greatly helped the Business users and Zonal heads in their analysis, target adherence and decision making.
  • We leveraged the Azure Cloud platform and its services such as Data Factory - for performing the necessary data connectivity to source through Full and Incremental modes and perform Orchestration, Data Transformation and Data Preparation. Azure Data Lake was used as a storage layer and would have the landing, curated and processed data layers. Azure SQL Database was the Data Query layer and Azure Databricks was used for data analytics workflow— Data Engineering Light workloads for data engineers to build and execute jobs.

Business Benefits

  • A full automated system of data load from source systems has facilitated centralized reporting and quick time to delivery.
  • A Cloud enabled solution- with high availability, ease of maintenance and optimized cost of infrastructure.
  • We have provided a system which proactively sends notifications on business deviations, and trend analysis of month-on-month visibility of their business performance.
  • The Leadership and CXO teams of the client have a greater visibility of their Business Units performance and track of KPIs.
  • They are now able to consistently measure the performance of every business unit on common goals and look at improvement measures to the units.
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