sexta-feira, dezembro 15, 2017

Process mining as the bridge between data science and process science


Process science is an umbrella term for the broader discipline that combines knowledge from information technology and knowledge from management sciences to improve and run operational processes


The ingredients contributing to data science


Data science

Data science is an interdisciplinary field aiming to turn data into real value. Data may be structured or unstructured, big or small, static or streaming. Value may be provided in the form of predictions, automated decisions, mod- els learned from data, or any type of data visualization delivering insights. Data science includes data extraction, data preparation, data exploration, data transformation, storage and retrieval, computing infrastructures, var- ious types of mining and learning, presentation of explanations and pre- dictions, and the exploitation of results taking into account ethical, social, legal, and business aspects.

The above definition implies that data science is broader than applied statistics and data mining. Data scientists assist organizations in turning data into value. A data scientist can answer a variety of data-driven questions. These can be grouped into the following four main categories:

  • (Reporting) What happened?
  • (Diagnosis) Why did it happen?
  • (Prediction) What will happen?
  • (Recommendation) What is the best that can happen?

An example of a customer journey illustrating the many (digital) touchpoints generating events that allow us to understand and serve customers better


Internet of Events