Dashboards, data visualisation & integration

Make analytical results available where your experts make decisions.

Your challenge

A working algorithm is not yet a usable application. Data flows, the interface and connections to existing systems must work together.

How IAP approaches it

IAP develops interactive dashboards, APIs and analytical data processing. Depending on the task, R, Python and C are connected to web interfaces. Development and operation are considered separately; refresh intervals, data volumes and access are defined for the application.

Project deliverables

An interface with the data views and integrations you need, together with documentation and onboarding. IAP can integrate the application into your environment and complete acceptance with your IT team. Your organisation or operating partner takes responsibility for subsequent operation.

Read the technical detail ↓

Methods and technical detail

From R, Python and C to a business application

Defined interfaces connect the analytical code to the web application. IAP’s documented architecture uses Angular for the frontend, Phoenix for APIs and PostgreSQL for persistent data. The appropriate components for your project depend on your existing IT environment. In the decision support system for Oilprice.com, this includes automated data ingestion, local preprocessing, model calculation and presentation in a protected dashboard. Local applications can also be delivered as a Docker container with a browser interface, as in the sales-forecasting prototype.

Manage data volume and computational cost

C/C++ optimisation, processing on demand and parallel computation can reduce memory requirements and execution time. The published memshare package enables shared memory across parallel R processes. Data volume, memory demand, refresh interval and runtime are assessed for the specific workflow.

Interfaces, acceptance and handover

APIs enable further analyses to be connected and results to be provided at the required resolution. Separate development and operating environments support checks before delivery. IAP develops and integrates the agreed scope; access, documentation and operating responsibility are handed over to your IT team or operating partner.

Methodological sources

Thrun, M. C., Stier, Q. & Ultsch, A. (2023). Interactive Toolbox for Two-Dimensional Gaussian Mixture Modeling. In: Amini, M.-R., Canu, S., Fischer, A., Guns, T., Kralj Novak, P. & Tsoumakas, G. (eds.), Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2022, Grenoble, France, September 19–23, 2022. Lecture Notes in Computer Science, Vol. 13718, pp. 658–661. Springer Nature Switzerland.

Interactive modelling of two-dimensional data distributions through a graphical interface for expert-guided Gaussian mixture modelling.

Springer · Interactive Toolbox ↗

Thrun, M. C., Pape, F. & Ultsch, A. (2021). Conventional Displays of Structures in Data Compared With Interactive Projection-Based Clustering (IPBC). International Journal of Data Science and Analytics, 12(3), 249–271. Springer.

Interactive visualisation and clustering that allow domain experts to identify and assess data structures and influence assignments.

Springer · Interactive Projection-Based Clustering ↗

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Commissioned development · decision support

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The right form of handover

Option 1

Prototype for your IT team

IAP investigates the problem, develops and evaluates the approach, and hands over the agreed prototype with documentation. Your IT team takes responsibility for further product development and operation.

Option 2

Application through integration

IAP develops the agreed application, including its interface and integrations, connects it to the intended workflow, and completes acceptance and handover. Your organisation or operating partner takes responsibility for subsequent operation.

Project stages and indicative timing →

Which decision do you want to improve?

In a free, non-binding 20-minute introductory discussion, we clarify your objective, starting point and a useful next step.

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