8 min read
AWS (Amazon Web Services) is Amazon’s cloud computing platform, providing a range of services that help developers build scalable and robust applications. The services available range from data storage to machine learning, artificial intelligence, analytics, and Internet of Things technology.
This barely scratches the surface of the offerings.
Among other reasons, organisations use AWS to increase the speed and agility of their services. In a cloud-based environment, resources are just a click away – there’s no need to order a new physical server, install a hard drive and RAM, install an operating system, etcetera, etcetera. Adding a new resource can be as simple as clicking a button in a dashboard.
Our first event was Data: The Genesis for Invention, presented by Swami Sivasubramanian, the Vice President for Data and Machine Learning at AWS.
Swami’s talk touched on some of the available services on AWS and the value they can add to an organisation. For example, AWS’ data warehouse platform, Redshift, can process exabytes (that’s a lot – 1 exabyte is over 1 million terabytes) of data daily, without performance ramifications.
AWS SageMaker, a machine-learning solution, makes over 1 trillion predictions a month. Users can build and train custom models that utilise data to make accurate, value-adding predictions and insights that can improve business operations and processes.
Swami ended the talk by reminding listeners that 'individuals create the sparks of innovation'. It’s the responsibility of leadership to empower individuals to make data-driven decisions that drive organisations forward.
The next event, Building modern data analytics architectures on AWS, was a hands-on demonstration of a modern clickstream analysis architecture using AWS Services, presented by Marco Tamassia, a Senior Technical Trainer at AWS.
Marco’s demonstration revolved around tracking the clicks of a user on an imaginary pizza shop webpage. This was a slightly more technical talk, focusing on how to configure an event-driven serverless architecture that operates well at a high scale of usage.
For me, the key takeaway from this talk was about building systems at scale – using decoupled components in an event-driven fashion can prevent some of the problems that appear when using slightly more traditional approaches.
If your business processes a lot of incoming data from varying sources, you can leverage the power of AWS to streamline your business processes around that data. This could allow you to make more effective, data-driven decisions that push your organisation forward.
If you currently have a lot of data in different places, a data warehousing solution utilising Redshift and QuickSight might make your data analysis processes a lot more straightforward.
I attended this event with my colleague Harpreet, another Full Stack Developer here at Ginger Root. Here’s what he thought:
'In today’s world, data is a commodity. Our clients require insights into their data which helps inform their decision making, in return generating growth. For developers, AWS enables us to spend less time building and maintaining technologies and more time on providing value out of data for our clients. I strongly believe that with these skill sets in our bag, we can provide more value for our customers, which is more than just software development. We can build scalable and high-performing solutions, generate data strategies and provide deep insights on our client's data.'
AWS Case Studies provide a lot of interesting real-world challenges that were solved using AWS. You can read more here: https://aws.amazon.com/solutions/case-studies
If you think AWS could help you or your business but you’re not sure where to start, we’ll be more than happy to offer our support.