Predictive analysis is becoming a fundamental tool in many fields.

In a time when data is omnipresent, the goal of predictive analysis is to use this data to learn from the past in order to predict events to come. Automation and optimization processes, decision making support, financial profit and cost reduction are the main advantages that come from predictive analysis.

The list of fields affected by this new technology is extremely diverse. In this list are production chains. Indeed, stock management and the logistical chain are optimized thanks to machine learning and artificial intelligence tools. In an entirely different context that is marketing, predictive scoring, identification models and automated segmentation are the main areas where predictive analysis is used. Another affected field is the machine industry. The Internet of Things (IoT) combined with the concept of industry 4.0 makes this field extremely interesting for the use of artificial intelligence tools. In particular the sensors that are placed on the engines collect raw data that is very valuable.

Predictive maintenance – which consists of detecting anomalies or anticipate failures – is basically made possible thanks to the combination of these technologies.

Of course, predictive analysis requires specialised skills in the complementary field of statistics, machine learning, programming and data valorisation. Mathematical knowledge of algorithms is also vital in order to make the most of each of the tools stated above. Data valorisation is also essential at the start of a Big Data project, in particular in predictive analysis projects. Its goal is twofold: first extract as much data as possible and second to transform it into information that is easy to manage in predictive models.


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Use Cases


Predictive Maintenance

The possibilities linked to predictive maintenance are numerous: anomaly detection, engine health monitoring, failure and breakdown prediction. Based on the engines’ raw data record, our team of engineers creates tailor-made artificial intelligence models specifically designed for your issues.


Sales Prediction

Anticipating future transactions, predicting the value of a shopping cart or predicting the return of an item. A few examples of marketing issues to which data analysis can bring solutions.


Price Prediction

Our team of engineers has developed a price predictive algorithm for items sold on the second-hand market based on text analysis. Please write to us for more details.