We delivered an integrated data, digital and cloud solution that worked in combination to solve IP Australia’s issues with their data and realise their vision. The three key stages of the solution were:
Prototyping the end state
Using RapidXP, a methodology for rapid experimentation and prototyping, we defined the end product. This approach focuses on validating the vision for the end product first before development to ensure speed to market and to minimise waste. We developed working concepts that IP Australia could interact with and confirm would meet the requirements and vision.
Laying the data foundation
Once we had a firm vision in place for the end product, our next task was to integrate data from multiple sources into one centralised database before overlaying the visual interface.
Our Data Analysts got to work building a robust and automated ingestion framework based on our model-less data warehousing methodology. The Servian Model-less Data Warehouse was a good fit for IP Australia as they have multiple data sources that change frequently.
This approach does not require upfront remodelling of data to fit into normalised or vault structures. Data is only modeled at point of delivery providing flexibility to change the data warehouse as business needs grow and change. The architecture retains the source system data model and minor transformations are then virtualised inside the Common Access Layer.
Developing the visual front-end application
Using AWS and Cloudflare, we developed a front-end app that is not only scalable with high availability and rigorous security, it also delivers outstanding performance. The build of the frontend and cloud infrastructure was completed using our Agile Scrum methodology, again ensuring waste was minimised.
The finished end product was IP NOVA, a visual and immersive search engine that helps users discover registered patents, trade marks, and plant breeder’s rights from IP Australia’s database.
IP NOVA delivers visualisation and business intelligence that enables end users to quickly gather information regarding a specific keyword such as location, industry or field of work, and perform customisable analysis from both a macro and micro perspective.
It encourages innovation by helping entrepreneurs, researchers, students and policy makers to identify IP information.