AWS provides a wide selection of analytics services that meet your data analytics needs and offer companies of all sizes and industries to drive demand with data. AWS offers data movement, storage, data lakes, big data analytics, and machine learning (ML). AWS analytics tools include custom-built services that provide the best price-performance, scalability, and lowest cost.

So, how can companies use AWS analytics tools, the features and services offered by AWS to improve their businesses?

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Data on Demand

One of the most advanced AWS analytics tools on the market is Amazon Redshift. It is a simple yet powerful data warehouse. It can run across regions and instances and run on SQL Server or MySQL database servers. It can also perform complex analytical queries as it incorporates various analytic tools such as Eloqua, Solr, and Kibana.

Redshift is a complex product, and as a result, it is extremely difficult to set up. Before Redshift, data warehouses could be complicated, expensive, and challenging to set up, which is why they weren't very popular. However, Amazon Redshift is managed through the AWS Management Console. 

When the Redshift server is launched, you must execute an IAM policy to delegate read/write permissions to other AWS services and users, such as a database server. The storage access rights granted in the IAM policy are not sufficient for users to download, store, or upload their data. You must also grant read and write access to the Amazon Redshift users to be able to use the features available on the Amazon Redshift server.

Another great feature of Amazon Redshift is that it allows for near-real-time analytics by running queries in real-time. This capability helps you to address your analytics problems fast.

AWS also has some simple and cost-effective solutions for data analytics.

Amazon Glacier allows businesses to store their data for extended periods, and they can easily transfer data at a low cost without paying for local disk storage. And even when the data is moved to another cloud, customers are charged for an incremental copy of the data stored in the Amazon Glacier instance.

AWS Comprehend helps companies perform natural language processing (NLP) and entity recognition in their data. This powerful tool can find an image of a cat in a photo library or a customer record in a CRM. And it can even translate text into another language.

Other solutions include Amazon Athena and Amazon SageMaker, enabling users to develop, deploy, and manage machine learning models quickly.

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Data Lakes

Amazon DynamoDB is a low-cost NoSQL document-oriented database service for storing and retrieving large datasets. It allows users to develop SQL-like queries, store large datasets across AWS, and use it for processing and analytics. DynamoDB enables users to create highly available tables, and it allows clients to change table schemas or their own database schema.

Storage Services

CloudFront and S3 help businesses serve content to customers in regions of the world. Amazon CloudFront serves static web content from Amazon Route 53, and it is available in US East (N. Virginia), US West (Oregon), and EU (Ireland).

Geographically distributed access is another instance when you need a low-cost solution that supports load balancing and caching. CloudFront allows you to distribute your content to different geographic regions.

S3 allows you to store all of your content, and it offers no-charge data storage. All you need to do is connect to S3 using the Amazon S3 client.

Visualization Tools

An emerging category of AWS analytics tools include visualization and image analysis. Visualization Tools on Amazon Redshift allow users to make it simple to explore data. These tools are web-based applications that enable you to create simple charts to share with others.

Amazon Image Analyzer helps you analyze the visual structure of the pictures you are uploading. This tool will help you understand your images more insightfully.

Other tools like Compressor and Filterer help you compress your data before uploading it to Amazon S3. This toolset is a powerful solution because it can compress your data 10x.

Amazon Cognito allows you to create a new identity for yourself or a team on Amazon WorkSpaces. This utility allows you to create a new identity that does not share any information with Amazon WorkSpaces.

Data Discovery

Amazon Memory Bin is shared searchable storage for any amount of data that you might need. It can be a store for production data and metadata or any unstructured data in Amazon S3.

Developers can easily create fast, scalable queries using Amazon DynamoDB in near real-time.

Other solutions include Amazon ElastiCache, an in-memory cache that stores many small objects and makes them available quickly and in near real-time. AWS HANA provides a database service for Amazon's scale-out cloud offering, including Amazon RDS and Amazon S3.

Amazon Snowball is a secure and easy way to move data from a relatively small and controlled collection to a destination where it can grow larger. Amazon Snowball works with Amazon S3 and Amazon Glacier.

They can use it to copy and move a variety of data types, including large volumes of video, photos, and even large databases. Amazon Snowball transfers all files and folders in a virtual machine, and customers don't have to re-upload files if they want to continue working with a file.

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Data Security

Data security is another area in which Amazon's AWS has excelled. Businesses can leverage AWS's security features, including Amazon CloudWatch, Amazon VPC, Amazon SQS, Amazon EBS, Amazon S3, Amazon SimpleDB, and the Amazon Cloudfront service.

Amazon CloudWatch is a system monitoring service that monitors the health of services and components in AWS.

Amazon VPC provides customers with dedicated network connectivity to services in multiple Availability Zones.

Amazon SQS allows you to schedule, monitor, and configure queuing systems in AWS.

Amazon EBS is an inexpensive and reliable way to store data in AWS. Amazon EBS is your default storage choice for your data.

Amazon SimpleDB allows you to leverage the power of the SQL and database services in AWS.

Amazon Glacier is an ultra-high-performance cloud file system service that provides near real-time access to your data from on-premises and hybrid clouds. Amazon Glacier provides faster backup and remote backup with reduced cost and increased reliability.

Other security-related solutions include Amazon Route 53, Amazon CloudWatch, and AWS Identity and Access Management.

Other Services

There are other advanced AWS analytics tools like Amazon Relational Database Service (RDS), Amazon DynamoDB, Amazon Web Services Identity and Access Management service, and AWS Management Console.

Amazon WMS is a platform to run managed database services and enable Amazon RDS, Amazon EMR, and Amazon Aurora to run on a private cloud infrastructure.

Amazon DynamoDB makes it easy to create and maintain rich data applications. It comprises three components – DynamoDB Server, DynamoDB Client, and DynamoDB Query Language (DQL).

Amazon CloudWatch provides information about your applications in real-time using Amazon CloudWatch API. You can see trends and statistics by drill-down into the metrics.

Amazon EBS is used for accessing and storing data. Amazon EBS provides quick access to your data through Amazon RDS, Amazon EMR, and Amazon Aurora. Amazon EBS has native REST APIs that make it easier to access.

They also offer Amazon Kinesis for streaming data to another storage location. Amazon Kinesis Streams is used for streaming data and analytics to Amazon S3 and Amazon Glacier.

This streaming is a great way to analyze data, perform real-time interactive monitoring, and provide alerts for potential failures. Amazon Kinesis Logs, AWS Event Hubs, and Amazon Kinesis Analytics are used for capturing and processing event data from your applications.

Amazon CloudWatch Logs automatically collects application performance and usage metrics and keeps the data organized and available in a single place.

Amazon CloudWatch Events automatically aggregates metrics from the CloudWatch dashboard to build event logs. You can configure CloudWatch to send the event logs to AWS ELB for Elastic Load Balancing, Amazon SNS for sending the events to Amazon S3, or an Amazon Kinesis Stream for sending the event data to an Amazon Kinesis Data Stream.

There are other data visualization and analytics tools that you can use to look at and analyze your data. Additional tools are intended for developers. 

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Conclusion

Customers desire to keep up with rapidly evolving technologies and trends. Therefore, businesses need to continuously stay up to date with the latest trends and techniques to ensure they keep up with the rest of the world.

The most effective way for businesses to leverage AWS analytics tools is to implement these platforms as a technology to help them boost their efficiency, profitability, and performance. Doing so helps develop new strategies that could help in their sales, and it provides them with crucial information to stay up to date with their competitors.

By being able to leverage AWS analytics tools, businesses can easily access and analyze the right data and, in the process, stay competitive with the market. Get started with AWS analytics tools by visiting the AWS website.

To gain more AWS and cloud analytics skills, look at Simplilearn's range of AWS certification training courses and programs. They include our AWS Cloud Architect Master's Program, which rolls up a comprehensive set of skills and certifications into a single program.

About the Author

Stuart CrequeStuart Creque

Stuart is a storyteller, with a foundation in technology, marketing, and management. He tells business stories in the form of content that means something to both external clients and internal team. He has written, produced and directed short films and written the feature film The Last Earth Girl.

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