Harvesting & data modelling

To compete successfully in a data-driven world, it is no longer possible to rely only on internal data; external data sources must also be leveraged. For this reason, we use numerous techniques and approaches to collect data:

• Extraction and analysis from online sources
• Open data, JSON, CSV, EXCEL
• Interfaces for importing data from corporate systems
• Web platforms for data collection

The data collected must be organized and structured in order to be analyzed. Database design, data cleaning routines and rollback procedures are essential to ensure scalability over time. This is why we pay great attention to the design phase of each specific solution, ensuring analysis speed, ease of maintenance and data consistency over time.

Data analysis

We apply different methodologies and techniques for data analysis with a multidisciplinary approach.
Statistical analysis, clustering and processing algorithms, together with machine learning approaches, make it possible to identify hidden patterns within data sets, as well as phenomena and information useful for monitoring and decision-making.
At this stage, contact with the client is essential in order to grasp the key elements of the context and implement data mining models capable of responding as effectively as possible to specific needs.