Our Process.

As every project is unique and has its own complexity, we partner and collaborate with our customers to ensure that each step of the overall project is tracked through sprint cycles, and each iteration is drafted and approved at agreed milestones. A typical project will involve six key steps to completion.

A Brief Overview of the Data Visualisation Process

Consult and Define Key Objectives.
During a consultation we collectively agree a set of key objectives with our clients. This will include identifying stakeholders and potential sources of data as well as confirming how insights are to be shared at the end of the project. Prospective timelines and required resources will also be confirmed.

Research and Collate Datasets.
We work with key stakeholders to find and select the most appropriate data for the project. This stage will determine whether we need to build a database and apply more detailed modelling techniques to achieve our objectives.

Prepare the Data.
Using tools such as Alteryx, Tableau Prep or SQL we can optimise the process to categorise, group, clean and join datasets to prepare for analysis. For smaller projects we can prepare and aggregate data in Excel ready for use in a visualisation programme.  

Explore, Analyse and Build Data Models.
We can start building some simple charts in Alteryx or Tableau to identify trends and patterns. This can provide some insight into which predictive data models we can test and apply to further enrich our analysis.  

Validate Data Back to Source.
When the data has been cleaned, prepared and predictive models have been built we check findings back to the source data and adjust any aggregations or data models to ensure that data integrity is maintained at each stage of the process.

Visualise, Present and Distribute Insights.
Using best practice data visualisation techniques we create stories and dashboards in Tableau, Power BI, PowerPoint, Illustrator and InDesign and share our insights with customers on their preferred platform.