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Data Science

Representative Work

Using Modern Data Engineering to Enable the Mission

A large US government agency recognized that their legacy data architecture, and its encompassing data pipelines, and data exchanges were very expensive and time-consuming to maintain and extremely difficult to evolve to meet new mission requirements. More significantly, the legacy data architecture was hindering their ability to produce intelligence products in support of mission-critical decisions.

An Axiologic Solution assessment identified a series of significant deficiencies:

  • Non-standard approaches for data pipelines/ETL, data integration, data fusion
  • Inconsistent approaches for data sharing, data access, and data security
  • Inefficient usage of different storage technologies
  • Lack of data standards, including security tagging

Axiologic Solutions implemented the following improvements:

  • Created standards based (REST, SOAP) application programming interfaces to access various data sources
  • Standardized the ETL pipelines using best practice patterns and standard technologies
  • Added machine learning and natural-language-processing capabilities to enhance ETL, data analysis and data access integrated search, data, and analytics capabilities into a user-friendly GUI that delivered critical intelligence in minutes instead of days.
  • Established more efficient use of data storage based on the size and types of the data.

The new data architecture has proven to significantly reduce labor and storage costs. Most importantly, mission leaders now have access to higher-quality data intelligence at their fingertips.

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