With data science you can have smart analyzes carried out by software. The Data Science process consists of a cycle of steps. Data is generated and stored in databases at any time of the day. In order to obtain the correct predictions, you must determine which data you will use. Rearranging, filtering and transforming data is done through programming. We use languages such as Python and R to transform data into models that can be used to make predictions.
Data science in practice
Just like in business intelligence (BI), data science is about analyzing and managing data, gaining insights and presenting them visually. This is mainly done with an understanding of “what happened” and “why it happened”. What data science adds to this is predictive analysis and artificial intelligence (machine learning). These techniques are intended to predict “what will happen”. Our consultants worked on the following concrete use cases of data science:
- Detecting financial services fraud by identifying abnormal transactions
- Improving the sales organization by making recommendations for customers based on previous purchases
- Optimizing the supply chain by predicting the optimal routes for tank containers
- Estimating of the amount of temporary workers needed in the coming period, based on the expected number of orders
- Reserving transport volumes with road and air carriers, based on the expected volume of expected orders