Gradient Victor garcia 0y L6n Xhn0p I unsplash Stripe

Better BI Decisions through Automated Reporting

Practice Areas

  • Data Engineering
  • Strategic Consulting

Business Impacts

  • Improved report quality
  • More effective decision-making

Challenges

  • Inadequate data quality and report refresh rate
  • Outdated, Excel-based manual process for business-critical reporting

Technologies

  • Microsoft Azure
  • Power BI

Background

Our client, a major player in the European tobacco industry, wanted to improve their reporting process. To meet the demands of a rapidly evolving market, they need to constantly change their product range, which makes it necessary for decision-makers to have access to accurate and timely insights to promote effective planning and execution of business strategies. However, the existing reports serving the European headquarters required a lot of manual work to prepare, and their quality regularly fell short of management’s expectations. To ensure that their BI environment would better serve the decision-making process, they reached out to Starschema for consulting services.

Challenge

An assessment of our client’s BI pipeline revealed that the quality and speed of business-critical reports were held back by two main issues. One was inadequate data quality, which resulted from the lack of a central data source – some reports were pulling data directly from the source system, while others relied on temporary report-serving layers, where non-transparent transformation processes occasionally resulted in data quality degradation. The other issue was outdated reporting production processes in certain branches, which were still Excel-based and largely manual.

Solution

Our client chose to implement a new, comprehensive BI strategy to improve operations from data delivery to report building. Since accurate data is essential to effective reporting, the first step was to improve data quality. We identified ETL issues and definitions for certain KPI and dimensions as the causes of data quality degradation, primarily due to a lack of standardized definitions across the client's branches in the various countries of operation.

The Starschema team suggested introducing data use based on the client’s global data warehouse instead of the direct use of different source systems. This enabled the European headquarters to directly source the exact data they need for reporting instead of relying on aggregate data from country-level sources. Leveraging this data warehouse as a single source of truth, our team developed new general BI concepts and rules to introduce a reporting governance framework. Key elements of this framework include a data layer that provides reusable data to serve different reports by pre-calculating metrics to make it easier to create new and ad hoc reports, as well as new reporting standards and dedicated roles in the report implementation process with appropriate access and license controls.

The team then reverse-engineered the production process of eCommerce reports to map and review the various steps involved and used the insights gained through this review to optimize report production following the new reporting governance framework. To ensure data quality retention throughout the reporting process, we put in place a series of data quality checks based on the reference data of the source systems.

The solution also introduced Power BI as a standardized data visualization platform. The client had already used the tool for global reporting needs, but the old, fragmented BI system made it necessary to maintain Excel-based manual tasks for certain local-level reports. Using the new reporting framework, we extended the client’s Power BI deployment to include these lower-level reporting instances, which helped integrate a broader range of reports into the headquarters’ BI infrastructure and automate previously manual processes. Finally, after revamping eCommerce reports, we leveraged the new framework and operating model to develop sales tracker reports.

Outcome

The solution enabled the client’s management to make better-informed and more timely business decisions based on accurate and easily accessible data. With the introduction of Power BI-based automated daily report generation in place of the earlier time-consuming, manual reporting process, reporting staff can now handle higher value-added tasks: by not having to manually extract the necessary data and build reports on a case-by-case basis, they can dedicate their time to extracting insights from data and communicating them effectively.

As a continuation of the project, Starschema will support the client’s business and IT staff to develop additional reports and introduce a new, Snowflake-based data warehouse to serve the sales department.

Telco Location Data Monetization

A global telecommunications company opened a new revenue stream and made it profitable in just two years.

IoT Data Lake on Azure Infrastructure

A leading European logistics company increased profits by using vehicle telemetry data to optimize routes and driver performance.

Cloud Security Best Practices That Organizations Often Overlook When Migrating

This white paper goes beyond cloud providers' documentation to introduce best practices that will help your organization ensure a comprehensive security solution for a cloud environment at optimal long-term cost. 

A Better View of Operations for A Glimmer of Hope

A Glimmer of Hope, an American non-profit philanthropic organization, generates large volumes of data during its day-to-day operation, and wanted to effectively track the outcomes and impact of their programmatic work, improve operational efficiency, optimize costs and allow donors to see the full impact of their donations.