
Yelp migrates from on-premises Hadoop cluster to Amazon EMR to support big data processing for features like location recommendations, top searches, and ads, scaling to handle over 30 terabytes daily.
Netflix uses Amazon Kinesis Data Streams to analyze VPC flow logs in real time, enriching data with application metadata to improve efficiency and reduce latency across microservices.
Automate video content indexing for c-span with amazon rekognition, boosting searchability and discoverability across eight networks while reducing indexing time to a third of manual effort.
Explore how business intelligence on AWS uses Amazon QuickSight to integrate disparate data sources, create scalable dashboards with drag-and-drop visuals, and leverage SPICE for fast analytics and automatic data replication.
Amazon Web Services (AWS) offer a unique opportunity to build out scalable, robust, and highly-available systems in the cloud. This course will give you an overview of all of the different services that you can leverage within AWS to build out a Big Data solution. We'll not only detail the use cases and limitations of each of the services, but also highlight particular cases where services may integrate to solve particular Big Data problems. Sections include real-world case studies that show how companies are actually using AWS today to solve their Big Data problems.
We will cover Big Data services in the following areas:
Serverless Architectures
In-depth case studies cover how real companies have leveraged the AWS cloud to build out Big Data solutions, such as:
Learn more about how to solve Big Data problems using the world's biggest cloud computing platform!