Journey To Modern Data Landscape + Executive Reporting
Building a cloud-based data landscape connected with their source transaction systems to avoid any modifications on numbers reported to executives
- Identifying data sources as information was scattered across multiple system.
- Data Uniformity was missing as each system was following different naming convention, and project master data was not maintained at a single source
- Manual reporting to Executive on monthly basis
- Conducted business workshops with business units reporting frequently to Client’s leadership, to identify and prioritize business KPIs
- Conducted workshops with source systems to define API or database connections to extract data and load in Azure data lake
- Azure Data Factory, Azure Data Lake, Data Bricks, Azure Synapse, and Power BI are selected technology options.
Key Value to Business:
Reduction in data manipulations by collecting the data points directly from transaction systems
Visibility and accessibility of Projects performance KPIs across LOBs in one view
Master data management concepts reduced the confusion in business around projects and customers
Cost visibility and usage of data landscape by Business units are clearly visible
Notebook structure of Dashboard with a Home page and Separate pages for each Business Unit.