CAVI (Cooperative and Automated Vehicle Initiative) project is being developed by TMR (Transport and Main Roads) which mainly focuses on new vehicle technologies including safety mobility and environmental benefits onQueensland Road. Their Goal is to test cooperative and automated vehicle technologies that make roads safer by contributing towards a vision of zero road deaths and serious injuries on the state’s roads.
Cloudten was involved to assist TMR with the Industry best practices and to review their current Data analytics pipeline and their large datastore
A large Australian federal government agency was seeking to gain greater business value and deeper insights into its wide and diverse range of disparate data assets. In addition to uplifting their advanced analytics capabilities, the business was looking to use the data lake to provide a wide range of real-world benefits including improved fraud detection, enhanced market awareness and predictive modelling in areas such as superannuation, mortgages and business lending.
They launched an open tender in 2019 to partner with a trusted data services provider to design, build and manage an enterprise grade Data Lake that incorporated best of breed tools and was capable of passing an independent IRAP security assessment toPROTECTED grade.
Cloudten won this competitive tender and has been working with the client on an ongoing basis to design and deliver the platform. We currently have an established 8 person team consisting of Data Architects, Engineers, Analysts and Data Scientists working closely with customer business and IT teams.
Our customer was looking to migrate their aged data warehouse platform off locally hosted physical and virtual infrastructure into a fully managed cloud environment that enabled them to both horizontally and vertically scale their dynamic workloads.
One of the key challenges of working on data warehouse projects is the timely, secure and precise transfer of large amounts of information from local data stores to cloud hosted network storage. In addition to the initial bulk transfer, the near real time synchronisation of deltas must be catered for throughout the staged migration process.
News Corp were having throughput and performance issues in their high volume, mission critical AWS infrastructure and were hitting capacity limits on a daily basis.
Cloudten was commissioned to perform an in depth analysis of their environment and provide tangible recommends to improve performance.
Cloudten was originally engaged by Origin Energy over 4 years ago to perform some of the initial design and delivery work for one of Australia’s first Redshift implementations.
This environment has now grown to become one of the largest data lakes in the country. It provides real time analytics capabilities that enable Origin customers to effectively query and model their energy usage and projected spend. It has also expanded to includeSnowflake and AWS Aurora.
This customer was looking to migrate their entire public website infrastructure from a third party hosted virtual platform into the AWS cloud to leverage the benefits of scalability and flexibility. As part of this process they were looking to implement DevOps best practices to automate and streamline their build and deployment pipeline. This involved a complete website redesign and the introduction of new tools sets and technologies to leverage maximise benefit from cloud infrastructure. The challenge was to cut online services over in a seamless manner whilst ensuring that the customer experience and the end to end site performance was not adversely effected.
RMS had a large amount of structured, semi-structured and non-structured residing in a range of formats and locations (both internal and external). None of this data was centrally aggregated and it was consequently impossible to gain insights from the combined data. They wanted a cloud-based data lake solution that could scale up and down in terms of storage and capacity.
Insurance & Care NSW (iCare) is one of Australia’s largest general insurers. Currently, iCare’s data team has workflows consuming more than 20hours of time for data processing, model training and data consumption. Also, there was a requirement to migrate their current training and deployment solution to AWS Cloud. They needed a solution to minimise the time required to execute their ETL jobs and to move these jobs to AWS. This will help getting more reliable and faster input data into iCare’s Qlik application.