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Data Mining & Enterprise Information Management (EIM)

Data Security graphicData Mining
Our approach to data mining and data science is centered on predictive modeling; applying data mining techniques and algorithms to create mathematical formulas to forecast and segment future events. Data mining provides the  rules and patterns for the analytic problems trying to be solved, using historical data. Our application of these findings to the current business challenges delivers powerful results for your organization.

Blue Canopy is committed to providing clients with next generation data mining, specifically Machine Learning techniques using Amazon Machine Learning (AML). AML provides visualization tools and wizards that can guide us through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology.

Enterprise Information Management
Big Data is the focus on managing the volume, variety, velocity, and veracity of data. The antithesis to establishing Big Data still lies with driving and delivering analytic value to the consumer and providing, “data that’s fit for use.”

Deploying Big Data Analytic platforms (like Hadoop) without a carefully designed and holistic approach to Enterprise Information Management (EIM) can leave valuable opportunities unaddressed. Blue Canopy EIM for Big Data framework leverages a Data Management Association (DAMA) Data Management Body of Knowledge (DMBOK) foundation, while providing further EIM augmentation for Federal standards, such as the Intelligence Community (IC ITE), White House Open Data Policy, and Big Data implementation lessons learned. Our proven approach of using EIM to unlock the power of Big Data enables better decision making across the enterprise.

Blue Canopy EIM provides a holistic approach that covers a broad range of factors, important for effectively managing data and information, while allowing for customization:

  • A consistent and efficient way of assessing the current practices and defining the desired state of maturity
  • Provides for continuous customer involvement, leading to a higher level of satisfaction, as well as more realistic and relevant data strategy and road mapping
  • Provides guiding principles during efforts to implement and improve Big Data and Analytics projects
  • Fully compliant with industry Best Practices such as DAMA DMBOK2, the U.S. Intelligence Community (IC-ITE), and White House Open Data Policy
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