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
- 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.