Last quarter of 2017 brought US$1.3 billion to Amazon Web Services (AWS) cloud platform which was greater than the combined return of four of its competitors namely- Microsoft, Alibaba, Google and IBM. It is worth noting that this lead has encouraged AWS to enter into the field of Big Data Analytics, Artificial Intelligence and Internet of Things (IoT). Earlier AWS’s portfolio included Infrastructure as a Service (IaaS) and Platform as a service (PaaS) offerings only. After it already claimed the cloud computing market, AWS is extremely enthusiastic about exploring new areas. And to appropriate this, it has put at disposal number of branch services divided specifically for data analytics, AI and IoT.
AWS in Data Analytics
• Amazon Elasticsearch Service
With built-in integration to Kibana and Logstash, Amazon Elasticsearch comes with real-time analytics delivery and easy to use APIs. It can be utilized for log analytics, full-text search and application monitoring. It provides free access to elasticsearch APIs to integrate the code already in use.
• Amazon Athena
Amazon Athena has this incredible query running service where you only pay for the queries you run and that too on a platform as easy as SQL. It allows you to analyze data on Amazon S3 using SQL. It is serverless that brings it into the category of those with absolutely zero infrastructure requirements. The fact that it uses SQL makes it accessible to anyone with a basic knowledge of query. This also reduces the overhead costing of the database administrator.
• Amazon Kinesis Data Firehouse
It helps the users to analyze data with the already present business intelligence tools and dashboards. It allows you to load streaming data into analytics tools. Apart from this, it loads streaming data onto Amazon S3, Amazon Redshift, Amazon Elasticsearch Service and Splunk. The amazing technique of minimizing data before loading it reduces the amount of storage leveraged.
• Amazon Kinesis Data Streams
It helps you build your own application to analyze streaming data for customization needs. It can collect humongous data from various sources at one time like websites, transactions to be further analyzed.
• Kinesis Data Analytics
It facilitates real-time insights from streaming data and that too only with the use of SQL. It further allows you to build applications to query streaming data. This ensures that customer requests are answered promptly.
AWS for IoT
• AWS IoT Core
It is a cloud platform that allows connected devices communicate and function among themselves and with other cloud applications. Talking about the storage, it can store huge amount of data and send the same to AWS endpoints after processing them. To keep track of all your devices, AWS IoT Core gives you the pleasure of doing that without having them connected.
• AWS IoT Device Management
Its major task is to let you remotely manage your IoT devices. Moreover, it also facilitates the remote registration for the devices which then can be monitored, organized and controlled via AWS IoT device management console. It also lets you group your devices and cater to their functionality.
• AWS IoT device defender
The specific task of the aforesaid feature is to allow you to secure your fleet of IoT devices. It keeps your IoT in compliance with the security policies and keeps a continuous track of them to not make them deviate. Device identity, other authorizing modules, all come under security policies. It reminds you in case of a breach of security policy for you to attend it.
• AWS IoT analytics
As the name suggests it allows you to analyze all your data from various IoT devices making you free from the headache of cost or complexity. It brings you the most reliable and easy way to analyze the IoT data in order to gather insights. Due to the harsh source, IoT data is often corrupted and unstructured which is why the normal analytics tools fail to structure and organize it.
• AWS Greengrass
It is majorly for the connected devices wherein it allows them to run on AWS lambda functions for synchronization and uninterrupted inter-device communication. Apart from this, it offers facilities like local compute, messaging, caching, and sync for the connected devices.
• AWS IoT 1-Click
It helps in triggering the AWS Lambda functions to perform a specific task. Specifically, it makes this task comparatively easier for simple devices. Simple devices are usually cloud-connected.
• Amazon FreeRTOS
Based on FreeRTOS kernel, Amazon FreeRTOS works on microcontrollers. It acts as an OS for microcontroller thereby making low-power and small devices easy to program, connect and manage. It has amazing software libraries that make it easy for the small devices to connect to AWS cloud services.
AWS in Artificial Intelligence
In the field of artificial intelligence, AWS has launched various services for quaint needs and requirements.
For seamless speech-to-text capabilities and services, there is Amazon Transcribe. It also provides services for the audio files stored in Amazon S3.
For high-quality and error-free translation, AWS has Amazon Translate. It can handle and translate relatively large volumes of data.
Amazon Comprehend is a Natural Language Processing service that utilizes machine learning algorithms to extract relevant phrases, text groups and then organizes them into customized topics as the end result.
Amazon Rekognition allows analyzing images and videos. You just have to feed the image or video and it will automatically scrutinize it for any negative or positive insights. It also provides facial recognition services.
In order to build conversational interfaces using voice or texts, Amazon Lex is the solution. It makes use of ASR (Automatic Speech Recognition) for speech to text conversion. It uses Natural Language Understanding for analyzing and manipulating the input for producing results.
Amazon Polly allows building applications for text to speech conversion. It uses deep technologies that make the end result having uncanny similarities with a human voice.
Amazon Sagemaker is a knight in shining armor for developers and data scientists. It facilitates the building, training and deployment of machine learning models.
When the developer intends to enhance their machine learning skills they turn to AWS DeepLens. It is a deep learning enabled wireless video camera that comes with video tutorials, hands-on exercises on pre-built models for developers to get hold of it.