Top 10 Analytical AWS Services

With Data & Analytics being baked into many of our core services, we aim to deliver some of the most innovative solutions when it comes to interpreting the data your business provides. But data itself is simply a set of qualitative or quantitative variables. Without the necessary means to interpret it, it can often be underutilised and wastefully neglected in modern cloud businesses.

As a Premier AWS Consultancy, we’re fortunate enough to have access to some of the best tools in the trade, able to manage, learn and interpret data and analyse it for smart, automated decision making.

In this post, we’re looking at some of the most used AWS services in Analytics and offering a breakdown of the top 10 and what each does.

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage and you pay only for the queries that you run.

Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds. With Athena, there’s no need for complex extract, transform and load (ETL) jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets.

Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to create a unified metadata repository across various services, crawl data sources to discover schemas and populate your Catalog with new and modified table and partition definitions and maintain schema versioning. You can also use Glue’s fully-managed ETL capabilities to transform data or convert it into columnar formats to optimize cost and improve performance.

Amazon EMR

Amazon EMR 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. You can also run other popular distributed frameworks such as Apache Spark, HBase, Presto and Flink in Amazon EMR and interact with data in other AWS data stores such as Amazon S3 and Amazon DynamoDB. EMR Notebooks, based on the popular Jupyter Notebook, provide a development and collaboration environment for ad hoc querying and exploratory analysis.

Amazon EMR securely and reliably handles a broad set of big data use cases, including log analysis, web indexing, data transformations (ETL), machine learning, financial analysis, scientific simulation and bioinformatics.

Amazon CloudSearch

Amazon CloudSearch is a managed service in the AWS Cloud that makes it simple and cost-effective to set up, manage, and scale a search solution for your website or application. Amazon CloudSearch supports 34 languages and popular search features such as highlighting, autocomplete, and geospatial search.

Amazon ElasticSearch

Amazon ElasticSearch Service makes it easy to deploy, secure, operate and scale ElasticSearch to search, analyze and visualize data in real-time. With Amazon ElasticSearch Service, you get easy-to-use APIs and real-time analytics capabilities to power use-cases such as log analytics, full-text search, application monitoring and clickstream analytics, with enterprise-grade availability, scalability and security. The service offers integrations with open-source tools like Kibana and Logstash for data ingestion and visualization. It also integrates seamlessly with other AWS services such as Amazon Virtual Private Cloud (Amazon VPC), AWS Key Management Service (AWS KMS), Amazon Kinesis Data Firehose, AWS Lambda, AWS Identity and Access Management (IAM), Amazon Cognito and Amazon CloudWatch, so that you can go from raw data to actionable insights quickly.

Amazon Kinesis

Amazon Kinesis makes it easy to collect, process and analyze real-time streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key 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. With Amazon Kinesis, you 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 Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.

Amazon Kinesis currently offers four services: Kinesis Data Firehose, Kinesis Data Analytics, Kinesis Data Streams and Kinesis Video Streams.

Amazon Kinesis Data Firehose

Amazon Kinesis Data Firehose is the easiest way to reliably load streaming data into data stores and analytics tools. It can capture, transform and load streaming data into Amazon S3, Amazon Redshift, Amazon Elasticsearch Service and Splunk, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today. It is a fully managed service that automatically scales to match the throughput of your data and requires no ongoing administration. It can also batch, compress, transform and encrypt the data before loading it, minimizing the amount of storage used at the destination and increasing security.

You can easily create a Firehose delivery stream from the AWS Management Console, configure it with a few clicks and start sending data to the stream from hundreds of thousands of data sources to be loaded continuously to AWS—all in just a few minutes. You can also configure your delivery stream to automatically convert the incoming data to columnar formats like Apache Parquet and Apache ORC, before the data is delivered to Amazon S3, for cost-effective storage and analytics.

Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics is the easiest way to analyze streaming data, gain actionable insights and respond to your business and customer needs in real time. Amazon Kinesis Data Analytics reduces the complexity of building, managing, and integrating streaming applications with other AWS services. SQL users can easily query streaming data or build entire streaming applications using templates and an interactive SQL editor. Java developers can quickly build sophisticated streaming applications using open source Java libraries and AWS integrations to transform and analyze data in real-time.

Amazon Kinesis Data Analytics takes care of everything required to run your queries continuously and scales automatically to match the volume and throughput rate of your incoming data.

Amazon Kinesis Data Streams

Amazon Kinesis Data Streams is a massively scalable and durable real-time data streaming service. KDS can continuously capture gigabytes of data per second from hundreds of thousands of sources such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs and location-tracking events. The data collected is available in milliseconds to enable real-time analytics use cases such as real-time dashboards, real-time anomaly detection, dynamic pricing and more.

Amazon Kinesis Video Streams

Amazon Kinesis Video Streams makes it easy to securely stream video from connected devices to AWS for analytics, machine learning (ML), playback and other processing. Kinesis Video Streams automatically provisions and elastically scales all the infrastructure needed to ingest streaming video data from millions of devices. It also durably stores, encrypts and indexes video data in your streams, and allows you to access your data through easy-to-use APIs. Kinesis Video Streams enables you to playback video for live and on-demand viewing and quickly build applications that take advantage of computer vision and video analytics through integration with Amazon Recognition Video and libraries for ML frameworks such as Apache MxNet, TensorFlow and OpenCV.

Amazon Redshift

Amazon Redshift 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. Redshift delivers ten times faster performance than other data warehouses by using machine learning, massively parallel query execution and columnar storage on high-performance disk. You can setup and deploy a new data warehouse in minutes and run queries across petabytes of data in your Redshift data warehouse and exabytes of data in your data lake built on Amazon S3. You can start small for just $0.25 per hour and scale to $250 per terabyte per year, less than one-tenth the cost of other solutions.

Your Next Analytical Step

With so much abundance of choice when it comes to analysing your companies data, why not team with a specialist in data, fluent in the services above?

Here at Firemind, we relish any opportunity to harness the power of data for a client and make it work for you, not against you. Get In Touch today and begin your data journey with us.