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Data Journey: From A to Z



Reporting & Analytics

The Challenge

Our client sought a tailored Business Intelligence (BI) solution, necessitating the development of a comprehensive database infrastructure integrated with a custom web-based dashboard. The project entailed designing and implementing the database infrastructure to meet the client's specific requirements, ensuring optimal data organization, retrieval, and analysis..

The Solution

We aggregated data from diverse sources, obtaining information through various channels, including direct access to platforms and reception of a segment via email, specifically vendor-supplied data. For platforms with direct access, we leveraged an API to seamlessly integrate the data into our PostgreSQL database, serving as our designated data warehouse. Given that the data received via email was unprocessed, we implemented a Python code to scan and modify the information systematically, minimizing the need for manual intervention and reducing the overall time invested. Post-cleansing incorporated the refined data into our PostgreSQL database. To link our data to BigQuery, we employed Google Cloud services as an intermediary to transform the data originating from PostgreSQL. The data's journey, from its inception to its final repository in BigQuery, underscores the efficiency of our daily data pipeline. This automated process meticulously navigates through each stage of data transformation. The entire pipeline operates automatically on a server deployed remotely. This deployment guarantees the consistent and automatic execution of the job, facilitating daily data updates and streamlining data management in our remote environment.

The Result

The client expressed immense satisfaction with a tailored system designed exclusively to meet their unique requirements without incurring additional charges for extra services. What's even more pivotal is our commitment to employing best practice methods, ensuring the project's robustness and readiness for any potential additional requests in the future. A significant focus was placed on the meticulous setup of databases within our warehouse, emphasizing the importance of well-organized, encapsulated data primed for potential multi-tenancy scenarios. This preventive measure positions us to incorporate new users should the need arise. This mini-project serves as a testament to our comprehensive understanding of the entire process, from raw data handling to creating a bespoke final dashboard. Achieving such results requires technical expertise, a profound understanding of the data context, and the ability to present the most pertinent information effectively.


Google Cloud

Transforming the PostgreSQL data to match our needs


Google Analytics

Using GA4 API to
connect to dummy
analytics account



Usage of BigQuery to streamline and construct custom queries to match our needs



Using PostgreSQL as a destination, and data warehouse



Visualization of the data withing the custom created dashboard


Custom API

Custom APIs are created to call upon the BigQuery data

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