Practice Areas

Open Data has been building predictive models since 2001 for a wide variety of industry sectors, including financial services, online advertising, direct marketing, and health care.

Our practice areas include:

  • Predictive modeling – building predictive models to increase revenues, decrease risks, or improve business processes.

    • Response modeling – building predictive models to predict whether a prospect will respond to an online offer, a direct mailing offer, a call center offer, etc.
    • Risk modeling – building predictive models to identify fraud, compromises, threats, attacks, and related areas.
    • Health and status monitoring and data quality – building predictive models to identify problems and potential problems with data quality or the health of a system.
    • Customer relationship management (CRM) – analyzing customer data to improve revenues and profitability.
    • Data from supply chain systems – analyzing data from suppliers to improve logistics, inventory, and utilization.
  • Analytic architectures and infrastructure.

    • Cloud-based analytics – developing and deploying analytics for clouds, such as analytic architectures based upon Hadoop, Sector/Sphere and Amazon’s EC2 and S3 services.
    • Analytic architectures – planning and designing analytic architectures, including analytics for single projects, analytics for the enterprise and SOA-based analytics.
    • Open source analytics – Open Data has deep expertise in open source analytics. A basic open source analytic stack includes MySQL (or PostgreSQL), Python (or Perl) and R and is sometimes abbreviated MPR. For specialized solutions when this standard MPR analytic stack is not adequate, Open Data also uses the open source, PMML-compliant Augustus platform.
  • Analytic strategy.
    • Open Data helps companies develop an analytic strategy.
    • Open Data assists companies evaluate technology and opportunities in analytics and related areas.