Case Study: Data Management and Visualization Project

The customer was navigating a complex digital transformation involving an ERP system upgrade and the rollout of Industry 4.0 tools for a new automated distribution center. The primary challenge was managing data quality across multiple systems, particularly for product SKUs, reporting, and dashboards. With various data sources that needed integration, the organization recognized the need for a comprehensive data solution.

To address these challenges, the company brought in a Data Architect and Data Visualization expert who initially began exploring visualization options. However, the consultant quickly realized that the fundamental issue lay in the data model itself. Working with Snowflake as the data warehouse and Tableau for visualization, the expert pivoted to focus on building a robust data lake/lakehouse model.

The approach prioritized data foundation over immediate visualization. The consultant first worked on consolidating and cleaning data from multiple sources, creating a unified and reliable data infrastructure. This meant standardizing product information, resolving inconsistencies, and creating a coherent data model that could support accurate reporting and decision-making.

Once the data was properly prepared and structured, the consultant began developing the reporting functionality. The goal was to create dashboards and reporting tools that would provide meaningful insights for the organization. By taking this methodical approach - first fixing the data, then building the visualization - the project ensured that the resulting reports and dashboards would be accurate, reliable, and truly useful for strategic decision-making.

The project ultimately demonstrated the critical importance of a solid data foundation in digital transformation efforts. By investing time and expertise in data modeling and integration, the organization set itself up for more effective use of its Industry 4.0 tools and improved overall operational intelligence.