Big Data Specialty Course Conclusion

3m 52s

This course has enabled you to recognize and explain the AWS big data services that are available and how to use those AWS services together to create Big Data solutions.

We covered the six domains of the big data specialty exam outline with lessons, labs, and quizzes.

For domain one we explained the various data collection methods and techniques for determining the operational characteristics of a collection system. We explored how to define a collection system able to handle the frequency of data change and the type of data being ingested. We identified how to enforce data properties such as order, data structure, and metadata, and to ensure the durability and availability for our collection approach.

Domain two of the Big Data Specialty course focused on storage. In this group of lessons, we outlined the key storage options for big data solutions. We determined data access and retrieval patterns, and some of the use cases that suit particular data patterns such as evaluating mechanisms for capture, update, and retrieval of catalog entries. We learned how to determine appropriate data structure and storage formats, and how to determine and optimize the operational characteristics of a Big Data storage solution.

In domain three of the Big Data Specialty course, we learned how to identify the appropriate data processing technologies needed for big data scenarios. We explored how to design and architect a data processing solution, and explored and defined the operational characteristics of big data processing. We delved into the various processing services available focusing on Amazon Kinesis, Elastic Map Reduce and Amazon Rekognition.

For domain four of the Big Data Specialty course, we learned how to determine the tools and techniques required for data analysis. We explored how to design and architect an analytical solution, and how to optimize the operational characteristics of the Analysis System using tools such as Amazon Athena and Kinesis.

In domain five we learned how to determine the appropriate techniques for delivering the results/output of a query or analysis. We examined how to design and create a visualization platform using AWS services, and how to optimize visualization services to present results in an effective and accessible manner using Amazon Quicksight.

Data Security
In this lesson, we examined how to determine encryption requirements and how to implement encryption services. We examined how to choose the appropriate technology to enforce data governance, and Identify how to ensure data integrity while working with Big Data solutions.

About the Author
Learning paths

Andrew is fanatical about helping business teams gain the maximum ROI possible from adopting, using, and optimizing Public Cloud Services. Having built  70+ Cloud Academy courses, Andrew has helped over 50,000 students master cloud computing by sharing the skills and experiences he gained during 20+  years leading digital teams in code and consulting. Before joining Cloud Academy, Andrew worked for AWS and for AWS technology partners Ooyala and Adobe.

Covered Topics