Data Architecture Modernization

The Data-Centric Manifesto posits that data is the center of the universe, and the trends around Data Science support the value proposition of data. Trends around adopting Data Governance is a reflection of organizations having increasingly complex data architectures, and the critical importance of quality data. Organizations require comprehensive capabilities and processes around data; the DMBOK Wheel summarizes the challenges.

This project:

  • Hired dedicated Data Architects to help lead the data architecture modernization initiative
  • Rationalized feedback with DMBOK to develop vision, do a gap analysis, and prioritize
  • Partnered with the new Enterprise Data team to promote Data Governance
  • Explored new solutions, conducted proof of concepts, and purchased new capabilities
  • Established a Community of Practice for Data Architecture to communicate new capabilities, best practices, and discuss challenges

Benefits included:

  • Standardized on tools and platforms
    • Provided uniform and secure access to data through a Data Virtualization platform, connecting SQL, non-SQL, and Data Lake data sources
    • Introduced a cloud data warehouse with an astonishingly low TCO and impressive performance
    • Connected a Data Science platform for efficient machine learning and artificial intelligence projects
    • Initiated the consolidation of several proprietary master data management systems into one industry leading Enterprise Data Management platform
    • Shifted consumers to leverage a real-time data distribution platform
  • Published data models and metadata for core enterprise data
  • Defined SLAs around critical data sets and optimized processes
  • Empowered users and promoted self-service, rather than relying on expensive, overloaded IT
  • Saved days of unnecessary data pre-processing, helping teams efficiently run machine learning models
Nifty tech tag lists fromĀ Wouter Beeftink