Our Process

Data Science is a discipline and, thus, requires a comprehensive team of multidisciplinary resources able to work through thoroughly-checked processes.

Our process allows the team to repeat its successes and correct its mistakes, extracting valuable information for the company, also carrying out a more efficient work.

Learn more about our processes...

Analysis

Business Understanding:

It is during this key interaction phase that our experts gain the knowledge of Customer Business Strategies, Goals, Priorities, Issues, and Needs. Here, first scenarios and sketches of Use-Cases and Data Analytics take shape. Even the journey of Data Science begins at this stage.

Data Understanding:

This is a critical phase where we look for existing Data Ecosystems (Sources, Accessibility, Structure, Definitions, etc.) as well as for tools and processes. A Business-oriented map of Data journey is drawn while IT processes and resource allocation strategies are identified and assigned.

Modelling

The modelling step is the one that will require the biggest effort in terms of time spent on tests and developments.

Data Preparation:

Here, Data Scientists need to be sure to have the correct data so as to create a good model and know how to clean data correctly not to corrupt the model.
Having reliable data is a crucial part of this step.

Model Definition:

In this stage, our Data Scientists are ready to create a model that best fits your needs and data. Trying out several models they work hard to find the one that best fits your expectations.

Value

This last step is mandatory to check whether reports resulting from the work previously done will deliver the value the customer is expecting from our services.

Model Evaluation:

Our Data Scientists continuously test and verify the quality of the model before deploying or presenting it. Here, they make sure the model answers the business questions defined at the beginning of the process. Such a stage is strategically important since our Data Scientists could find new interesting questions to answer.

Deployment:

This action can be done through APIs that call your model or, simply, documenting results to executives through custom reports.

Exploit the Data of your company

Associate Partner
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Technological Partner