How it works
Data science at your fingertips
Whether a beginner in analytics or a machine learning expert, HyperCube is designed with you in mind. It is the Swiss Army knife of data science, combining proprietary and open source code to deliver a wide range of data analysis features straight out of the box or as business apps, customized just for you.
Upload data from a wide range of storage and connectivity sources – including SQL/NoSQL databases and via APIs – quickly and simply thanks to HyperCube’s easy-to-use interface.
Use built-in filters to make data work harder. Define word sets and tags, or slice and dice the data by timestamps such as season, week and working day. We call it data wrangling.
Figure out which parts of your data matter most using HyperCube’s advanced univariate tools to analyze and visualize by variable, module or value range.
Apply business rules to quickly understand relationships within your data. Use this multivariate analysis to identify influential drivers.
Use visualization techniques including heat maps and clusters to explore the density, size and purity of data. Apply local constraints and clustering algorithms.
HyperCube allows you to create word sets from scratch or from existing collections. Build visualizations to bring insights to life and reuse text analysis for multiple projects.
Examine and display data in multiple formats, including Sankey charts, tree maps and bubble charts.
Combine machine learning algorithms and open source libraries to build unrivalled analytics solutions.
Power users can take advantage of advanced features such as grid search and minimization. Direct access to multiple libraries are available via HyperCube APIs.
Select the format suited for your legacy IS and embed in a snapshop the great models designed and tested with HyperCube
Here comes the techie bit. Welcome to the HyperCube technology stack:
Responsive design (HTML5/CSS)
Proprietary algorithms using data mining techniques including classification, prediction, subgroup discovery and supervised learning
Best of breed Python and Spark libraries including Spark ML, scikit-learn and NLTK
Encrypted communications (TLS 1.2)
Token authentication (JWT)
Encrypted data storage
Data storage by location (based on AWS or Azure capabilities)
AWS / Azure
Kubernetes / ECS