Insight in data

Transforming raw data INto insightful data products

From dashboarding, business intelligence, data science, machine learning to Artificial Intelligence, analysing data to gain insight can be simple but may fast  become quite complex. We help you not only get a grip on your data but also with making your data insightful.

We have years of experience in designing dashboards, enterprise BI solutions and analysing data using algorithms. We use a proven best practices approach based on the international recognised method CRISP-DM.

In six incremental steps from initial idea to practical insights

1. Requirements analysis. Understanding what the business needs;
2. Data understanding. Investigating what data exists in the organisation and the quality of overall data governance and data management;
3. Preparation of the data. This includes everything from cleaning up data, completing missing data and assigning metadata to integrating data from different sources into new data sets;
4. Modeling the data. Building and (in the case of data science and AI) training the data models and data science models;
5. Evaluating the data products. In this phase, you look at which of the data products you have developed best fit the demand in practice;
6. Usage and data and model management. In this phase, the business starts using and managing the data products and continues improvement is implemented.

Risk-free use case-driven approach

This approach is incremental, cyclical and based on use cases, so results can already be achieved in a short period of time, with low risks and