AWS Analytics - A comprehensive guide to Amazon Web Services Analytics Services
By Naveen |
Last updated on December 20, 2023 |
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In this section of the AWS tutorial, you will learn about AWS Analytics and its various tools. You will learn about Amazon EMR, AWS Data Pipeline, Amazon Kinesis, AWS Machine Learning, and other tools that can help you transfer and analyze large amounts of data. You will also see examples of how these tools can be used in different applications.
AWS Analytics Overview
Services provided by AWS Analytics are as follows:
Data is organized and controlled by the Amazon Elastic MapReduce with the assistance of the Hadoop technology sharing deals. This tool simply sets up and manages the Hadoop framework. This tool controls the calculative assets and carries on the MapReduce process.
The flow of the data in larger amounts is done by Amazon Kinesis. We can transfer information from Amazon Kinesis to any storeroom such as AWS Redshift, EMR cluster, etc. Data Pipeline manages the transfer of information and also acts on them. The pipeline tells about various parameters like the input information, the terms, and conditions for the transfer, the location to where the data needs to be carried away, etc.
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Now, let’s see the properties of AWS Analytics tools.
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| Tools |
Description |
| Amazon EMR |
Amazon EMR uses Hadoop, which is an open-source framework, for managing and processing data and uses the MapReduce engine to distribute processing using a cluster. |
| AWS Data Pipeline |
AWS Data pipeline helps in regularly moving and processing data. Using a pipeline, you can define the input data source, the computing resources to perform the processing, any condition that must be validated before performing processing, and the output data location such as Amazon S3, Amazon DynamoDB, etc. |
| Amazon Kinesis |
It allows the real-time processing of streaming data at a humongous scale. You can also send data from Amazon Kinesis to a data warehouse, such as Amazon S3 or Amazon Redshift, or to an Amazon EMR cluster. |
| Amazon ML |
Developers can easily use Machine Learning technology for obtaining predictions for their applications by using simple APIs. |
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