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Fundamentals of Analytics on AWS – Part 1

This course is the first of two offerings designed to introduce learners to the current market trends in analytics. In Part 1, you will learn fundamental concepts such as types of analytics, the 5 V’s of big data, and the challenges associated with processing high volumes of data. This course also maps the 5 V’s of big data to AWS services for analytics and discusses how AWS provides the most comprehensive services on the market. Following completion of this course, learners are encouraged to continue their journey with Fundamentals of Analytics on AWS – Part 2 . Course level: Fundamental Duration: 2 hours Activities This course includes: lessons, videos, scenarios, and knowledge check questions. Course objectives In this course, you will learn to: Explain data analytics, data analysis, analytics types, techniques, and analytics challenges. Define machine learning (ML), ML on AWS, and different levels of AWS for ML services. Define the 5 V’s 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. Intended audience This course is intended for: Cloud architects Data engineers Data analysts Data scientists Developers Prerequisites We recommend that attendees of this course have: Reviewed AWS Cloud Practitioner Essentials or equivalent Course outline Section 1: Introduction Lesson 1: How to Use This Course Lesson 2: Course Overview Section 2: Analytics Concepts Lesson 3: Analytics Lesson 4: Machine Learning Lesson 5: 5 Vs of Big Data Lesson 6: Volume Lesson 7: Variety Lesson 8: Velocity Lesson 9: Veracity Lesson 10: Value Section 3: AWS Services for Analytics Lesson 11: AWS Services for Volume Lesson 12: AWS Services for Variety Lesson 13: AWS Services for Velocity Lesson 14: AWS Services for Veracity Lesson 15: AWS Services for Value Section 4: Conclusion Lesson 16: Quiz Lesson 17: Course Summary Lesson 18: Appendix of Resources Lesson 19: Feedback


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