Our AWS Certified Architects, Developers and Managed Services consultants can help you on your journey in the cloud.
We help you take advantage of cloud platforms such as AWS to support Big Data and Analytics solutions.
The AWS Practice Team can deliver strategic advice for organisations looking to utilise the cloud for Big Data and Analytics loads. Our services include:
We can help you design your solution architecture, taking into account your requirements and constraints around Data Volume, Data Latency, Fault Tolerance, Solution Availability and Security.
The AWS Practice Team helps delivering AWS Big Data and Analytics projects. Our services include: analysis, design, development, testing, optimisation and handover. Typical solution delivery projects include:
Different technologies need to be used when handling large Data volumes and/or when there is a need to analyse the data in near real-time.
AWS Kinesis Service Suite (real-time data processing) and AWS EMR (large data volume processing and storage) are key technologies for Big Data and Data Streaming use cases. AWS S3 is typically used in this architecture for persistent storage.
A Data Lake is used when there is a need to store large amounts of data in a way that will allow a wide variety of usage of data in the future. As opposed to a Data Warehouse, the data format in a Data Lake is not dictated by the usage by downstream systems. The data does need to be catalogued and searchable. Data Lakes normally include the following components:
Leverage AWS technologies to achieve both performance and simplicity, such as AWS Redshift, a fully managed petabyte scale Data Warehouse and S3, AWS Simple object storage used to land data extracted from Data Sources.
Many options exist for the ETL engine, either EC2 based using a RedShift dedicated ELT tool such as Matillion, leveraging AWS fully managed services such as Kinesis Firehose or Spark processing on EMR.
Similarly, there are many possibilities in the reporting and analysis area. A host of AWS Technology Partner tools are readily available on the AWS Marketplace. For a fully managed reporting and analytics capabilities, AWS Quicksight is another option.
Another increasingly popular building block of advanced Data Warehouse is AWS Lambda that gives server-less compute capabilities.
Below is an architecture Altis has implemented for a global company running around 1,000 restaurants in Australia. The client wanted to analyse billions of Point of Sale transactions using RedShift.
In this context, there were two main advantages in using AWS Lambda:
Mainly leveraging EC2 servers to allow any flavor of technology, solutions typically cover:
This approach is generally recommended in a lift and shift scenario where the solution hosted on AWS needs to be very close to the legacy on-premises solution.
After your solution is live in a Production Environment, our AWS trained and certified Managed Services team can provide support of your AWS hosted solution. Support typically includes:
Guillaume is the AWS Practice Lead at Altis and is part of our Sydney consulting team. Guillaume is a certified AWS Architect and has expertise in Big Data, Data Warehousing and Analytics.
He loves travelling and staying in a place long enough to discover the unexpected. Scuba and sport keep him fit and believing ‘all men who achieve great things have been great dreamers’ keeps him dreaming.
Tel: +61 2 9211 1522