Over the course of several years, our client had grown through multiple acquisitions in multiple countries around the world. They needed a solution to make their data more accessible, standardized, and accurate.

Client Challenge

Client Challenge – The client’s growth created a variety of issues that their existing platform could not handle effectively. The issues included:

  • Difficulty in integrating and reconciling data due to ​multiple IT systems and DBs​
  • Merging of inconsistent data sets leading to poor data quality & accuracy​
  • Lack of standardization in data format, structure and content​
  • Data privacy and security concerns​
  • Limited visibility into cross departmental data hindering decision making
  • Data silos and duplication of information

Milestone Solution

Milestone’s Digital Platform Engineering Services worked with the client and determined an AWS cloud-based platform (data lake) using cloud-native technologies and Spark would provide: a configurable ETL pipeline to handle different kinds of files​, support parsing of CSV, XML, XLSX and custom formats, anonymize ​PCI/PII data​, and transform data as needed. The solution also included an ETL framework to build self-healing data pipelines and support multiple sources and destinations, and in-built Datapost and intelligent orchestration capabilities.


The result was a tailored AWS data lake platform that:

  • Allowed data from six different business units to be integrated into one format and one Data warehouse​.​
  • Enabled data to be collected through files, database, Kafka streams, etc.​
  • Put data privacy and security checks in place to ensure PCI/DSS compliance​.
  • Integrated data across the merchant life cycle from marketing to servicing​.
  • Built-in data quality checks and alerts will be raised within the hour of an inconsistency.

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