Embracing a variety of tools and frameworks to present data in highly visual and meaningful ways.

The visualisation of data can often turn an incomprehensible set of numbers into a powerful story-telling tool, conveying insights to even the less data-literate people in a very short amount of time. It makes number, patterns and the insights held within them compelling, and deliver powerful business intelligence quickly and succinctly.

As a Design focussed consultancy, Deepend have long embraced the power of data visualisation, and have utilised it in a wide range of projects. From applying a customer centric lens to data visualisation for the likes of the Bureau of Health Information and the Department of Justice, to the use of interactive data to reinforce a key brand proposition of transparency for the likes of Active Super.

Our work has taken shape across industry leading data visualisation tools, such as Tableau and Power BI, to frameworks such as D3.js and HiCharts. In each project, we try to ensure that the data and the interactive lens that is applied to it is in service of key user needs and informational requirements.

Case Study - Active Super

Formerly Local Government Super, Active Super rebranded and relaunched, targeting a broader set of customers, focussing on ethical and environmentally conscious investment. With a new brand and a wider target market, it was critical that Active Super sought to reinforce its position, focussing on its key Brand attribute of transparency.

An opportunity was seen in the market for full transparency around investments, allowing customers to interrogate the makeup of each sub-fund, right down to the geographic location of investment and the ESG rating of each and every equity held. This took shape in the form of several interactive data visualisations. Data is automatically compiled from a variety of sources and stored in a web accessible repository. This data is then visualised via a custom designed instance of the Hi Charts tool. Users are able to drill down into the makeup of each specific.

The Bureau of Health Information

The Bureau of Health Information (BHI) is a board-governed organisation that publishes independent reports and data about the performance of the NSW public healthcare system. Having begun with printed materials only, its output has grown organically to now provide filterable access to an extensive range of data online. This extension of their key outputs has seen both their analyst and publishing teams stretched, as they look to manage increasing demands from customers for more interactive data sets.

Deepend partned with BHI to assess both the internal mechanics of managing such interactive data sets, and also the specific wishes of key end user groups. Conducting a range of qualitative and quantitative research, we ideated a future state solution that would meet the needs of user groups such as Media and Government, as well as addressed a high level strategy for restructuring the internal infrastructure to manage data storage ongoing.

Case Study - Department of Justice

The NSW Bureau of Crime Statistics and Research (BOCSAR) is a subdivision of the Department of Communities and Justice and is responsible for the processing and publication of data regarding the performance of the Justice system in NSW. In line with their internal charter to become more consumer focussed, they have been driving the development of a number of innovative interactive tools, allowing external users to interact with the data sets that they collate.

The first of these tools to be developed focussed on the visualising of data pertaining to Criminal Court Sentencing Data. The application presents data on court sentences imposed on offenders having proven court appearances in the NSW Local and Higher Courts.

Sentence information is provided across three levels of offence classifications (grouped by the Australian and New Zealand Offence Classification groups), and allows users to apply a number of filters to view sentencing outcomes specific to their data and information needs, including offender age bracket, Gender, whether the offender had any prior convictions, and whether the offender had served any time in prison previously.