Solutions Review editors compiled this list of the best AWS big data training and online courses to use when growing your skills.
The first major cloud computing provider, Amazon Web Services (AWS) combines over 100 distinct services that cover a wide breadth of cloud capabilities. AWS focuses heavily on infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) offerings, with an emphasis on providing virtual infrastructures and development tools, including storage, computing, database, mobility, and management services. The big data landscape is evolving in real-time, which has organizations scrambling to utilize their data architectures soundly. Coupled with this, Hadoop and the data lake have emerged as technologies no company can ignore.
With this in mind, we’ve compiled this list of the best AWS big data training and online courses to consider if you’re looking to grow your cloud data management skills for work or play. This is not an exhaustive list, but one that features the best AWS big data training and online co from trusted online platforms. This list of the best enterprise architecture courses below includes links to the modules and our take on each.
The Best AWS Big Data Training
TITLE: AWS S3 Basics
OUR TAKE: By the end of this project you will create an S3 bucket and will be able upload content to the bucket. You will also enable Encryption, Versioning, Static website hosting, and will create Lifecycle management rules for objects.
Description: In this 1-hour long project-based course, you will learn about AWS S3 and its features like Encryption, Versioning, Static Website Hosting, and Life cycle management. S3 stands for Simple Storage Service, it is an object-based storage service that AWS provides. You will need an AWS account to complete this project. All the resources used in this project come under AWS free-tier.
OUR TAKE: This course uses a combination of video-based lectures delivered by Amazon Web Services expert technical trainers, demonstrations, and hands-on lab exercises, that you run in your own AWS account.
Description: This course introduces you to NoSQL databases and the challenges they solve. Expert instructors will dive deep into Amazon DynamoDB topics such as recovery, SDKs, partition keys, security and encryption, global tables, stateless applications, streams, and best practices. This course can be applied to multiple Specializations or Professional Certificates programs
OUR TAKE: This module will help you understand how to create and operate a data lake in a secure and scalable way, without previous knowledge of data science. The training is instructed by Morgan Willis.
Description: This course is for professionals (Architects, System Administrators, and DevOps) who need to design and build an architecture for secure and scalable Data Lake components. Students will learn about the use cases for a Data Lake and, contrast that with a traditional infrastructure of servers and storage.
OUR TAKE: AWS architect Brandon Rich shows you how to configure object storage solutions and lifecycle management in Simple Storage Service. Students also learn how to migrate, back up, and replicate relational data in RDS.
Platform: LinkedIn Learning
Description: This course teaches system administrators the intermediate-level skills they need to successfully manage data in the cloud with AWS: configuring storage, creating backups, enforcing compliance requirements, and managing the disaster recovery process. The training can also be used as preparation for the Data Management domain within the AWS Certified SysOps Administrator exam.
TITLE: Amazon Web Services: Data Services
OUR TAKE: This course helps you explore your storage and framework options when working with data services on the Amazon cloud. This training is taught by working big data architect Lynn Langit.
Platform: LinkedIn Learning
Description: This course helps you navigate the options when it comes to file storage, relational and NoSQL data storage, data warehousing, graph and ledger databases, and data lakes. Plus, learn how to run open-source processing tools such as Hadoop and Spark on AWS and leverage new serverless data services, including Athena serverless queries and the auto-scaling version of the Aurora relational database service, Aurora Serverless.
TITLE: AWS DynamoDB Deep Dive
OUR TAKE: This intermediate-level course shows you how to develop applications on the AWS DynamoDB database. Updated in June 2019, this training touts an impressive 6 hours of instructional content.
Description: You will explore how to process a stream of updates to DynamoDB tables in real time, how DynamoDB works under the hood, how to use DynamoDB transactions, how other AWS services integrate with DynamoDB, and how you can use them to get the most out of it.
OUR TAKE: Datameer’s Andrew Burst shows you the fundamentals of big data on Amazon Web Services so you can understand which combination of products is best suited for your use case.
Description: In this course, you will learn foundational knowledge of big data concepts and the major big data services on AWS. First, you will learn all about core big data concepts, like data lakes, NoSQL and MapReduce. Next, you will discover the array of big data services available on AWS and how they tie together.
TITLE: Collecting Data on AWS
OUR TAKE: This course will help you understand the best ways to ingest data into AWS first by exploring how to collect data over a dedicated network or with hardware appliances. This is an intermediate-level training with nearly 140 minutes of content.
Description: Students will discover how to can migrate databases using the Database Migration Service and learn how to leverage the Amazon Kinesis family of services. Learners also gain the skills and knowledge of data collection on AWS needed to prepare their own data ingestion pipelines.
TITLE: Storing Data on AWS
OUR TAKE: By the end of this course, you’ll have the skills and knowledge of AWS data storage technologies needed to effectively design data-storage solutions on AWS. The intermediate-level training was last updated in July 2020.
Description: First, you’ll explore how and when to leverage Amazon DynamoDB for low-latency, highly scalable data storage and access patterns. Next, you’ll discover how to use Amazon S3 for both file and data storage. Finally, you’ll learn how to analyze different use cases for these services as well as other services that might play a role in the larger data storage picture.
OUR TAKE: This course will help you understand the possibilities of big data on AWS. This training is ideal for big data aspirants, AWS enthusiasts, software developers, architects, and analytic professionals.
Description: With the unstoppable growth in the organizations moving towards data science and big data analytics there is a need for trained professionals who are well versed with both big data and AWS technologies. This course helps the learners get the best of both worlds (big data analytics and AWS Cloud) to prepare for the future.
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