Delta Lake and warehouse design with advanced reporting in Power BI environment

The client

Edenred stands as a foremost provider of transactional solutions catering to companies, employees, and business partners globally. With a presence in multiple countries, Edenred offers an innovative spectrum of products and services.

Beyond merely facilitating transactions, Edenred builds strong collaboration with numerous corporate associates, ensuring optimized value propositions and enhanced business engagements. Their extensive service range not only underscores advanced transactional solutions but also embeds business process enhancement, insights, and consultancy, positioning them as a pivotal ally in the modern corporate landscape.

The challenge

• A suitable tool was needed to govern Key Accounts Managers, their progress and to track sales figures.
• Due to the nature of the client’s data, the highest security standards were required.
• The ability to conduct thorough data analysis and trends was required.

The solution

The solution contained up-to-date data that was loaded from the source systems and updated a minimum of 3 times a day and on demand. In addition, the solution presented measures with names in line with the accepted glossary established during the analysis phase.

The solution’s design harmonises the layout per Edenred’s guidelines for the colour palette and the use of the company logo.

To ensure that the data was correct in relation to the source systems, BitPeak solution verifies the completeness of the data at each stage of the ETL process, and information on incomplete data was recorded in the operational logs so that appropriate corrective action could be taken. Additionally, the solution prevented double loading of the same transactional data thanks to the mechanisms used, such as incremental feeds and business key recognition.

The use of the Power BI tool provided a number of functionalities, such as sorting, filtering, expand/download tables and charts, and users were also able to add their own calculated quantities based on the presented data and build charts themselves (self-service BI).

Reports included both current and historical data, which were displayed automatically according to previous arrangements and the selected time period. Additionally, through the usage of the latest UX practices, the reports were designed to be easily readable and understandable with minimal training, while providing broad range of information.

To realize our goal, we used the following tech stack:

• Python: for establishing underlying logic
• SQL: for data manipulation and definition
• Microsoft Azure services (ADL, ADF and Synapse): for storage and integration
• Power BI: for data visualization