Data Minimization for a US based service organization

Banking & Financial Services
Reduced data footprint results in cost savings, enhanced data security and privacy compliance, accelerated responses to data requests and strengthened customer trust.
The Case

The client, burdened by the vast accumulation of data across its applications and databases, faced challenges in managing data effectively, resulting in increased costs. They sought to understand data usage and apply proper purging and archival mechanisms, aligning with the data minimization principle to collect and retain only necessary data.


The Reflections team Executed Data Quality & Minimization practices including cleaning, classification, deidentification, and retention management. We implemented Data Governance policies aligned with business needs and compliance requirements, including the integration of payment data into the data management and governance framework to ensure compliance with financial regulations such as PCI DSS. We established a restoration plan, monitoring, and reporting mechanisms for continuous improvement.

Technology Stack

Python with Fast API for backend development.

PostgreSQL Database for data storage.

Open metadata for data cataloging.

Python Core for scripting and automation.

LLM (OpenAI) for advanced language processing.


This resulted in a significantly reduced data footprint leading to cost savings. Data security and privacy compliance were enhanced. The responses to data requests were accelerated. Responsible data handling led to strengthened customer trust.

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