A Chicago based food production client required a centralized, structured location for all of their data in order to maintain one source of truth across all departments, run accurate reports and gain business insights through advanced analytics.

The Problem

A Chicago based food production company wanted to empower their finance team with comprehensive data analytics and visualizations they could use to gain insights and drive better decisions.  Issues with their data however, made it nearly impossible to get the insights they needed and led to mistrust between the business and the IT department.

Data Issues:

  • Data was scattered in several disparate sources across multiple departments within the company.
  • Poor or inconsistent data quality and integrity.
  • Inconsistent business processes for entering and maintaining the data.
  • Antiquated reporting methods that resulted in poor reporting on crucial business metrics.

Our Solution

Our solution was broken down into 3 phases, integration of the existing data into a data warehouse, process improvement to ensure ongoing data quality, and development of advanced analytics dashboards.

Phase 1: Data Integration

The Aptitive used SSIS to integrate all of the data sources into a “data hub”, we then modeled and developed a data warehouse for advanced reporting and analytics.

Phase 2: Process Improvement

Once the data warehouse was complete, we worked closely with the business and IT stakeholders to define a data governance strategy and implement several process changes to ensure the data quality issues would not persist.

Phase 3: Advanced Analytics and Reporting

Following process implementation, we moved on to the front end. Using SSAS and PowerBI we were then able to create several reports and high-level dashboards to drive business understanding for the stakeholders.

The Outcome

The finance department executives went on to validate and implement the dashboards as the golden standard for their teams. The finance teams now use the reports to track their progress, make decisions, and aid in planning. In terms of continuity for the data, the improved processes and data governance policies that were put into place have improved the quality of the data substantially, and enabled new, more advanced types of reporting and analytics.

Client Industry

Food Production

Technology

SSIS (ETL)
SQL Server (DB)
SSAS (Tabular Model)
Power BI (Data Visualization)