Context & objectives

Our client, a key player in the professional matchmaking industry, requested that Agilytic deploy a comprehensive data warehouse (DWH) solution in AWS, complete with an efficient and streamlined ETL pipeline.

Without this infrastructure in place, the client faced significant risks, including stagnation in their business intelligence capabilities and missed opportunities for valuable analytics insights. Overall, inefficient data engineering practices could hinder their competitive advantage.

This strategic project was designed with three main goals in mind:

• Improved efficiency across their data operations

• Enhanced analytics capabilities that would unlock deeper business insights

• A more structured and sustainable approach to data management that would support their long-term growth objectives

Approach

The project was carried out in 2 phases.

In the first phase, the team evaluated the existing data model for the DWH to ensure alignment with the client's requirements. They selected appropriate cloud services tailored for the DWH deployment, choosing the ones provided by Amazon.

In the second phase, the core of the project involved building the ETL pipeline, establishing connections to various data sources, and integrating them with the DWH. The team used:

• AWS Glue for automated ETL

• Amazon Redshift as a scalable data warehouse

This approach allowed the team to efficiently handle large volumes of data while ensuring flexibility and scalability for future growth.

Results

The project yielded significant positive results for the client:

• Improved business intelligence reactivity through operations performed in the ETL instead of the BI tool, leading to more timely insights

• New opportunities for advanced analytics, allowing the client to leverage their data more effectively

• Enhanced structure in their data engineering activities

Overall, the data warehouse empowered the business with better visibility and improved decision-making capabilities. This gave them the ability to leverage advanced analytics for a competitive advantage.