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