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AWS Analytics

AWS Analytics can help your organization become a data-driven business. Focusing on the business outcomes and not the technology as well as paying for only what you consume are some of the benefits of AWS Analytics. Becoming agile and timely will give your organization a leg up it deserves.

To become a data-driven business, one must separate compute and storage. By separating compute and storage, your organization will be able to apply the right amount of computational power for the problem at hand and not over-allocate either compute or storage. There are five essential items your organization will do with data; ingest, store, analyze, and visualize.

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The following are all of the AWS Analytic tools to help you accomplish your goal to be a data-driven organization.

Amazon Athena
This is an interactive query service that makes it analyzing data in Amazon S3 using standard SQL. It is serverless, so no infrastructure is required.
Amazon CloudSearch
This cost-effective tool simplifies the set-up, managing, and scaling a search solution for your website or application.
Amazon Elasticsearch Service
This AWS tool makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero downtime. It offers open-source Elasticsearch APIs, managed Kibana, and integrations with Logstash and other AWS Services, enabling you to securely ingest data from any source and search, analyze, and visualize it in real-time.
Amazon EMR
This provides a managed Hadoop framework that makes it easy, fast, and cost-effective to process vast amounts of data across dynamically scalable Amazon EC2 instances. It is secure and reliable to handle a broad set of significant data use cases, including log analysis, web indexing, data transformations (ETL), machine learning, financial analysis, scientific simulation, and bioinformatics.
Amazon Kinesis
This tool makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. It offers vital capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. Your organization can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications.
Amazon Redshift
This is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake. It delivers ten times faster performance than other data warehouses by using machine learning, massively parallel query execution, and columnar storage on high-performance disk
Amazon Quicksight
This is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake. It delivers ten times faster performance than other data warehouses by using machine learning, massively parallel query execution, and columnar storage on high-performance disk
Amazon Quicksight
This tool makes it easy to deliver insights to everyone in your organization. It quickly creates and publishes interactive dashboards that include ML Insights. These dashboards can then be accessed from any device and embedded into your applications, portals, and websites.
AWS Data Pipeline
This is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. It helps you easily create complex data processing workloads that are fault-tolerant, repeatable, and highly available.
AWS Glue
This tool allows your organization to extract, transform, and load (ETL) services, making it easy for customers to prepare and load their data for analytics.
Amazon Managed Streaming for Kafka
This tool makes it easy for you to build and run applications that use Apache Kafka to process streaming data. It is an open-source platform for building real-time streaming data pipelines and applications. Your organization can use Apache Kafka APIs to populate data lakes, stream changes to and from databases, and power machine learning and analytics applications.
AWS Lake Formation
This tool makes it easy to set up a secure data lake in days. Lake Formation collects and catalogs data from databases and object storage, moves the data into your new Amazon S3 data lake, cleans and classifies data using machine learning algorithms, and secures access to your sensitive data.
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