National CAE Designated Institution
  • Classroom
Course Description

Data analytics is transforming business processes at organizations large and small. Through the fusion of siloed data across the enterprise with open data such as social media and public databases, a trained data scientist can identify efficiency and opportunity. This course will introduce participants to big data frameworks, open source analytics tools, design methodologies, and visualization libraries through hands-on case studies.

Learning Objectives

  1. Explain steps to clean and normalize data during fusion
  2. Define the analytics pipeline of ETL, analyses, visualization, and reporting
  3. Access open source data from social media (Twitter, Instagram, Facebook) and public databases
  4. Map analytics application requirements to big data frameworks and tools
  5. Utilize cloud-based tools such as AzureML for real-time predictive modeling
  6. Understand the limitations of data analytics algorithms
  7. Integrate science and mathematics into business processes

Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.

Feedback

If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.