Upgraded Manual Excel-Reporting to Centralized Power BI Reporting
Manufacturing
Schindler Deutschland AG & Co. KG
> 4000 Employees
SAP data exports (Excel, CSV, text files)
Manually maintained Excel sheets from different departments
Primary Challenge
The elevator company relied heavily on SAP for their backend operations but lacked direct database access to SAP tables. This forced various departments to manually download data in Excel, CSV, or text files and then combine them in their own Excel sheets, leading to significant manual effort and a high risk of errors.
Our Approach
We provided end-to-end support to automate and enhance the company's data processing, reporting, and analytics systems. Our focus was on implementing a robust ETL pipeline and establishing best practices for Power BI reporting. This included:
ETL Automation and Centralized Data Management:
Implemented a production-grade ETL pipeline using Azure Data Factory with proper environments for safe development, testing, and production deployment.
Collaborated with the internal RPA (Robotic Process Automation) team to automate data downloads, organizing them into specific folders and feeding into a centralized BI system.
Unified data from various reports, ensuring reliable data quality and reducing the manual workload of the team.
Building Power BI Reports with Best Practices:
Developed and delivered many of the company’s key internal reports in Power BI, following best-practice guidelines for design, structure, and data modeling.
Created a centralized data model that enabled quick and consistent report development.
Training and Knowledge Transfer:
Conducted training sessions to make the team self-sufficient in building and managing ETL pipelines using Azure Data Factory.
Delivered in-depth Power BI workshops, empowering the team to maintain and build reports following best-practice methodologies.
Created comprehensive guidelines for both Power BI and Azure Data Factory, ensuring long-term sustainability.
Ongoing Support and Development:
Provided continuous support and mentoring to ensure the team could effectively automate updates and create new reports independently.
Guided the transition from a trial-and-error approach to a structured, principle-driven method for both ETL pipelines and Power BI reporting.
Key Benefits
Our intervention led to significant improvements in the company's data management and reporting processes, including:
Automation of Data Processing: The ETL pipeline automated manual data handling, reducing errors and significantly speeding up data updates.
High-Quality, Consistent Reporting: Centralized data and Power BI reports built with best practices ensured reliable, high-quality output across the organization.
Optimized Report Development: The use of a structured data model enabled faster and more efficient creation of reports, reducing time spent on development and revisions.
Increased Visibility and Accessibility: Reports became easier to access and were automatically updated in real time, making critical data instantly available to stakeholders.
Empowered Teams: Through training, the development team became proficient in both Azure Data Factory and Power BI, enabling them to independently manage data pipelines and build reports efficiently.
Enhanced Decision-Making: Accurate, timely, and consistent data empowered decision-makers with better insights, leading to improved organizational outcomes.
