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Development of a scalable and distributed architecture


Parque Arauco




Santiago, Chile

Use Case

Data Analytics - Data Mesh


Parque Arauco is a renowned Chilean company that operates in the real estate and shopping center sector. It was founded in 1982 and has become one of the main developers and administrators of shopping centers in Chile and other Latin American countries. In addition to Chile, Parque Arauco has expanded its presence in other Latin American countries, including Peru, Colombia, and Uruguay. It has developed and operates shopping centers in these locations, establishing itself as a leading company in the region.

Parque Arauco stands out for its focus on the quality of its projects and its commitment to sustainability. The company has implemented various initiatives focused on energy efficiency, carbon emissions reduction, and the integration of sustainable practices in its operations.

Business Challenges

Parque Arauco faced challenges in its data journey towards the cloud, with high system segregation in parallel lines of business analytics.

The company managed multiple projects that took a long time to become productive, while others were canceled. Providing the required information to the business areas with accuracy and appropriate availability required significant human effort.

Proposed Solution

  • A comprehensive assessment of the current architecture was conducted, and a process of continuous improvement with greater efficiency in decentralized models was initiated.

  • A Data Mesh Serverless architecture was built, utilizing a central core of distributed storage across different domains (S3 buckets and Redshift data warehouse), processing data using Glue and Lambda, ensuring traceability and data governance with Lake Formation and logs stored in S3 and DynamoDB.

Results and Benefits

  • We achieved a scalable Data Analytics architecture capable of operating and sustaining a regional data ecosystem for Chile, Peru, and Colombia.

  • We transitioned from the traditional "turnkey" project approach to an incremental and value-driven work methodology.

  • The analytics team expanded by over 300% across various business areas, including Data Engineers, Product Owners, and Cloud Engineers.

  • We successfully revived stalled projects by migrating architectures and enabling evolutionary functionalities.

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