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.