Data Analytics on Streaming Data using Amazon Kinesis Data Analytics 

Netflix, one of the most popular internet television networks, delivers nearly 125 million hours of TV shows every day and has more than 100 million subscribers worldwide. The company needs to ensure that its customers have a great experience, watching high-quality content without interruptions or glitches.

But ensuring this can be overwhelming given the volume of data and the large client base. The company needed a real-time analytic solution that could quickly help identify issues to enable timely response for high availability and customer delight. The network was already using Amazon solutions for computing and storage and opted for the highly scalable Amazon Kinesis Data Streams to process multiple terabytes of daily log data and identify events within seconds of their happening. Kinesis also helped to improve efficiency, lower costs, and enhance resiliency.

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Amazon Kinesis is a cloud-based, managed, scalable service that allows real-time processing of streaming large volumes of data per second. Meant for real-time applications, it allows developers to consume large volumes of data from different sources and scale up and down as needed while running on EC2 instances.

A Serverless Solution

Amazon Kinesis Data Streams is a serverless solution that provides timely insights by collecting, processing, and analyzing streaming data in real-time without the need for provisioning or managing the capacity needed to run the applications. It can ingest data in any format, including videos, audio, application logs, website clickstreams, and IoT telemetry data in real-time and use it for analytics, machine learning, and other applications

It is a cost-effective solution allowing users to pay per use, thereby reducing ownership costs and improving RoI. It comes with built-in integrations with other AWS services to enable the creation of serverless, analytics, and application integration solutions on AWS fast. It captures gigabytes of data every second from several thousands of sources including website clickstreams, social media feeds, IT logs, database event streams, financial transactions, and location-tracking events, and makes it available quickly for real-time analytics. Some of the key uses include generating real-time dashboards, performing real-time anomaly detection, enabling dynamic pricing, and so on.

It uses Apache Flink, an open-source framework and engine, to process data streams to simplify the building, integrating, and managing of Apache Flink applications with other AWS services

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AWS Kinesis Data Streams Use Cases

Some of the common use cases of AWS Kinesis Data Streams include:

Real-time Data Analytics: Kinesis Data Streams allow parallel processing power adding value to the access to real-time data.

Real-Time Metrics and Reporting: Kinesis Data Streams allows the data collected or gathered to be used for reporting and simple data analysis in real-time.Complex Stream Processing: By developing Directed Acyclic Graphs (DAGs) from data streams and Kinesis Data Stream Applications, downstream processing through various Kinesis Data Streams Applications is possible. Some of the other use cases include

(i). building video analytics applications for video playback, face detection, security monitoring, machine learning, and other analytics.

(ii). Perform real-time analytics on data where batch processing was being used

(iii). Build real-time applications for various purposes, including application monitoring, live leaderboards, fraud detection, and so on.

(iv). Analyze streaming data from IoT device

Benefits of Amazon Kinesis Data Analytics

Using Amazon Kinesis Data Analytics solutions, users can experience the following benefits:

Powerful Real-Time Processing: The built-in functions in Amazon Kinesis Data Analytics facilitate filtering, aggregating, and transforming streaming data for advanced analytics. The streaming data is processed with sub-second latencies, allowing incoming data and events to be analyzed and responded to in real-time.

Prevent Data Loss: It prevents data loss through synchronous replication of the streaming data across 3 Availability Zones in an AWS Region. This data can be stored for up to a year and provided with multiple layers of protection against data loss.

Security: KDS aids in regulatory compliance by encrypting sensitive data and enabling access only with proper authorization. Server-side encryption and AWS KMS master keys provide data security at rest.

Easy to Use: The AWS SDK, the Kinesis Client Library (KCL), connectors, and agents help with quickly building streaming applications. Data processing is made easy with built-in integrations to AWS Lambda, Amazon Kinesis Data Firehose, and AWS Glue Schema Registry.

Elasticity: It allows the dynamic scaling of applications from megabytes to terabytes in an hour and from thousands to millions of PUT records within seconds. The throughput of the data stream can be adjusted at any time based on the input data volume.

Indium Approach to AWS Kinesis Data Streams

Indium’s data engineering team has experience in providing analytics solutions using streaming data for real-time insights and actions. Further, we are an AWS partner and have the expertise to create custom solutions using AWS Kinesis Data Stream to help businesses improve performance and customer delight. We leverage AWS’s complete set of pre-fabricated toolsets to spur businesses on the path of innovation and growth by making them agile, collaborative, and customer-focused. We can help businesses align the business’s strategic imperatives with cloud platform capabilities and leverage tools such as AWS Kinesis Data Streams to gain actionable insights and timely responses.


Author: Indium
Indium Software is a leading digital engineering company that provides Application Engineering, Cloud Engineering, Data and Analytics, DevOps, Digital Assurance, and Gaming services. We assist companies in their digital transformation journey at every stage of digital adoption, allowing them to become market leaders.