The White Box team can deliver the end to end solution; data architecture, data cleansing and manipulation, dashboard wireframes and build, data science techniques, strategic advice and implementation. We do all of this only with an understanding of your business and its objectives.
While projects change from client to client, data visualisation is a constant delivery each time and we are considered experts. As the people closest to the data, it is our job to explain and excite people about the potential for using their data.
Below is a selection of some of the tools and software we use with a brief summary of what they are used for:
Microsoft SQL Server / MySQL Building relational databases, data manipulation of multiple large tables, complex queries and creating datasets for analytical interpretation
R Open source statistical software. Building models (multiple regression, random forests, XGBoost, clustering, correlation, factor analysis and Chaid)
Python Has the same toolkit as R but also the benefit of being used by developers, so collaboration is potentially easier
SAS Data manipulation, complex queries, analytical queries and building models (multiple regression, clustering, correlation and factor analysis)
SPSS Data manipulation and building models (multiple regression, clustering, correlation, factor analysis and Chaid)
Excel Data manipulation, VBA coding and building bespoke interactive and dynamic reporting/dashboards
Dashboards and Business Intelligence
Tableau Very flexible and powerful. Has an emphasis on making your dashboard look very stylish.
Power BI Microsofts competitor to Tableau. It utilises the SQL engine, so the backend is impressive for live dashboards.
Qlik More of a traditional dashboard with the ability to drill down.
Google Analytics The 101 of website tracking software. We can help with setting up Custom Reports, Goals/Events tracking, Advanced Segments and detailed analysis of individual user web behaviour.
We have worked with all of the big cloud environments including managing the environment as a data warehouse solution to produce agile, on-demand analytics.
Amazon Web Services (AWS)