Fundamentals of Analytics on AWS – Part 1
Posted 2 days 2 hours ago by Amazon Web Services (AWS)
Discover big data and analytics solutions on AWS
Modern organisations require robust analytics frameworks to transform high-velocity datasets into actionable insights. Mapping the 5 Vs of big data to cloud architectures reveals how AWS handles complex data processing demands.
Explore data pipelines using AWS analytics services
Mastering storage, processing, and transportation options prepares practitioners to evaluate ideal AWS analytics solutions. Integrating ETL/ELT workflows and business intelligence tools ensures complete pipeline visibility and validates core skills.
You’ll access learning content and practical activities online through Amazon Web Services (AWS), alongside your FutureLearn course experience, giving you direct access to AWS learning as you progress.
This course is ideal for cloud architects, data engineers, data analysts, data scientists, and developers
This course is ideal for cloud architects, data engineers, data analysts, data scientists, and developers
- Explain data analytics, data analysis, analytics types, techniques, and analytics challenges
- Describe machine learning (ML), ML on AWS, and different levels of AWS for ML services
- Explain the 5 Vs of big data
- Explain common ways to store data, challenges, characteristics of source data storage systems, and available AWS solutions
- Explain data transportation, options for different environments, and available AWS solutions
- Define data processing, options for each type of processing, and available AWS solutions
- Identify different types of data structures, types of data storage, and available AWS solutions
- Explain where ETL and ELT fits in multiple places of the analytics pipeline, the elements of an ETL and ELT process, and available AWS solutions
- Explain the use of business intelligence tools to gain value from analytics, and available AWS solutions