You don’t have to take our word for it.

Here’s what a few of our DATA DRIVEN CUSTOMERS have to say about
The Data Foundry and D2E:

Sydney Swans logo

Sydney Swans and The Data Foundry

The Sydney Swans AFL Club (The Swans) wanted to move to making more data-driven decisions in their quest to excel on and off the field.  They engaged The Data Foundry (TDF) to build an AWS Data Lake based on TDF’s D2E framework, to unify data across its player development programs, so that their data was working as hard as their players and support staff.

For the project, TDF onboarded data from a variety of platforms, including the Protrac player tracking and analytics platform as well as building the initial AWS Data Lake, which became known internally as “Swan Lake”.

TDF worked with AWS and The Swans to establish an Amazon QuickSight capability to enable The Swans to build player insight dashboards.  Swan Lake was also connected to The Swans existing business intelligence toolset to allow for improved data reporting, data analytics, and data visualisation.

“We were connected with the TDF team via AWS and were immediately impressed with their energy, capabilities and client-first mindset. Paul Macey and the team spent the time to truly understand the needs of our high-performance environment, and delivered a product set that not only exceeded expectations, but was on time and on budget. We are already exploring opportunities to extend our engagement of TDF and look forward to the outcomes this will realise in 2023 and beyond.”

Drew Arthurson – Chief Operating Officer – Sydney Swans

As a result of the successful work to date, The Swans are now working with TDF on projects to onboard more datasets and provide additional capabilities, including a Player Readiness dashboard and enhanced performance analytics capabilities.

Department of Justice & Community Safety (Vic) and The Data Foundry

The Victorian Department of Justice & Community Safety (DJCS) engaged The Data Foundry (TDF) to connect a number of disparate data siloes by building an AWS Data Lake based on TDF’s D2E framework.

TDF onboarded data into DJCS’ Enterprise Data Lake (EDL) from a variety of platforms, ranging from field operations supporting Azure workloads to highly visible statistical workloads.

TDF also established an Amazon SageMaker machine learning capability to enable DJCS to improve its predictive COVID risk modelling capability.

“The Data Foundry (TDF) has been a highly valuable partner in delivering a complex enterprise data platform with very demanding security requirements. Throughout the project, we felt that DJCS and TDF were one team, allowing us to feel confident that we were fully supported in our endeavour. TDF were able to understand our diverse requirements and translate those into an effective and working platform that delivered high value to the organisation.”

Mark Dobroff – Senior Project Manager – Data & Analytics – DJCS

As a result of the initial successful EDL project, TDF has been consistently re-engaged by DJCS to further enhance the EDL, onboard additional workloads and re-factor them to take advantage of AWS’ cloud-native service capabilities.

RMIT University and The Data Foundry

RMIT University (RMIT) engaged The Data Foundry (TDF) to support the development of the RMIT Amazon Web Services (AWS) Cloud Supercomputing (RACE) Hub, using their D2E framework. The resulting solution was designed to provide scalable computing infrastructure to researchers and students at the university, allowing them to easily access the necessary compute resources for their tasks using an on-demand, self-service approach.

TDF built and implemented a pilot solution that became the RACE Hub, and assisted in onboarding the initial workloads from a variety of platforms, demonstrating the out-of-the-box capabilities and customisability of Service Workbench on AWS, and its suitability to meet RMIT’s research needs.

“The Data Foundry offered an exceptional level of expertise in an easily accessible manner. They know where to focus energy, what to prioritise and when to raise an issue. I’ve been very happy with their performance to date.”

Nick Balkin – Senior Project Manager – University Operations – ITS – RMIT University

The RACE Hub is currently being used by the Integrated Photonics and Applications Centre to perform compute-heavy and complex tasks, faster than was previously possible, in such applications as simulating and visualising the propagation of light on an integrated photonic chip.

Golf Australia Logo

Golf Australia and The Data Foundry

Golf Australia (GA) engaged The Data Foundry (TDF) to build an AWS Data Lake based on TDF’s D2E framework, to unify data across its athlete development programs.

For the project, TDF onboarded data from a variety of platforms, including three global golf ranking websites, the Australian golf handicapping service (GolfLink), athlete management software (i.e., Smartabase), golf technology products (TrackMan), and third-party data providers (DataGolf).

TDF established an Amazon SageMaker capability to enable GA to build predictive Machine Learning models and identify and track emerging golfing talent, in the lead up to the 2024 and 2028 Olympic Games. The Data Lake was also connected to GA’s existing Tableau toolset to allow for improved data reporting, data analytics, and data visualisation.

“The team from TDF were easy to work with, took the time to understand our desired use cases, and produced a high-quality solution. By reaching our target state of all data in one place, we can now automate manual processes and keep our team focused on what they do best: using a data-driven approach to produce world-class athletes. We recommend TDF to similar customers looking for a high-performing data and technology partner.”

Dr Jarred Pilgrim – Data & Analytics Manager – Golf Australia

As a result of the successful project, GA re-engaged TDF to onboard more datasets and build additional data-driven capabilities, including an Athlete Performance Portal, improved Data Curation, and enhanced Machine Learning capabilities.

The University of Melbourne and The Data Foundry

The Data Foundry (TDF) was initially engaged by the University of Melbourne (UoM) to support the marketing campaign associated with their Virtual Open Day project. TDF designed, built, documented and handed over a series of Amazon QuickSight-based dashboards that presented data elements sourced from a range of backend UoM systems. Since then, TDF has gone on to work with UoM on a number of other data-driven projects including data engineering, data pipelines, enterprise data lake, data onboarding and additional data visualisation solutions. They have integrated a range of backend systems into UoM’s AWS-based enterprise data lake (EDL) including Oracle, Salesforce, Google Analytics, Canvas, StudentOne, Facebook, LinkedIn, Campaign Manager 360, Sonia, Akamai and Cvent, as well as assisting UoM to implement a DataOps approach to managing the EDL, including supporting processes and toolsets.

“The team from TDF have become an integral extension of our team over a very short period of time. They are easy to work with, know their stuff and produce high-quality solutions and documentation. Our end-users love the way they just get the job done, without any fuss or unnecessary delay. TDF call themselves a Data Driven Company and they’ve certainly lived up to that reputation amongst my team. We would have no hesitation recommending TDF to similar customers looking for a trusted data partner that knows both the AWS and data space, inside out.”

Jason McKay – Director Strategy, Innovation & Assurance – University of Melbourne

RMIT Online Logo

RMIT Online and The Data Foundry

The Data Foundry (TDF) was engaged by RMIT Online to build an AWS Lake House comprising a Data Lake and Data Warehouse, together with an integrated catalogue that included their existing ELDAR data warehouse.

The project included onboarding data from a variety of platforms including Google Analytics, Facebook, and LinkedIn. An Amazon SageMaker capability was also established to enable RMIT Online to start building a range of Machine Learning models. The Lake House was also connected to RMITO’s existing Tableau toolset to support a more data-driven approach to reporting, analytics, and visualisation of the Lake House data.

“The Data Foundry has worked beside our fantastic data and tech teams in RMIT Online several times, lending a hand for heavy lifting projects, stitching different sources of data together and extracting powerful insights from it. As a digital business, data-driven insights underpin our student experiences. I could not recommend this team more highly, for having some of the best approaches, tech and skills anywhere, enabling RMITO and our accomplished data experts to take data-driven decision making to the next level.”

Helen Souness – CEO – RMIT Online

As a result of this successful project, RMIT Online went on to work with TDF to onboard more datasets, including their Canvas Learning Management System data and PeopleSoft (SAMS) Student Administration data.