Analyzing big data can optimize efficiency in many different industries. Improving performance enables businesses to succeed in an increasingly competitive world.

Analytics & Data Science 

In every company an immense amount of data is produced. Usually, this data is only used for the purpose for which it was collected. Sales figures for management and accounting, asset management data for inventory, and fault reports to track the progress of a report. It is often forgotten that this data contains much more information than just the immediate purpose for which the data was originally collected. All you need to do is unlock the valuable information from this data.


To transform available data into useful information, the right questions must first be asked. A clear and unambiguous set of questions is necessary to choose the right data to be used for analysis. For example, consider the simple question of where your customers are. If the underlying reason for asking this question is to know where you as a retailer need to ship your goods to then we choose the delivery address. If you want to know in which regions you need to do (local) marketing then we might better choose a billing address. This is obviously a simple example, but it shows that the background of the question is of great importance in choosing the right data for the analysis.

Once a clear question has been formulated, the data can actually be analyzed and visualized. cimt has experience in clarifying issues of various levels of complexity: from simple questions and building dashboards to complex cases where various scenarios must be calculated ad hoc. Depending on the issue, the right tool is deployed.

cimt is a partner of Looker: a Business Intelligence platform in which all results can be visualized in the form of dashboards or individual visualizations, and which can easily be shared with people inside and – if desired – outside your organization. In addition to Looker, we also support other business intelligence platforms such as Microsoft PowerBI, Tableau, Qlik and MicroStrategy.

Data Science 

When the data-related issues become more complex and need to be approached with scientifically supported methods, the work area of Analytics quickly shifts to Data Science. Consider solutions such as regression, dimensionality reduction and machine learning. These offer a solution for various use cases such as data deduplication, fraud detection, predicting maintenance of equipment, but also to analyze the buying behavior of customers so you can better respond to them.

cimt has experience in implementing various platforms in the field of data science. We bring extensive and industry independent expertise, backed by scientific rigor and deep knowledge of the latest techniques to design, build and deploy customized solutions.

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