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Glossary: Do you speak Insights?

12. May 2021

Theres Baumgartner

AI, big data, profiling - terms like these are on everyone's lips in the age of digitization & Elon Musk. But what do they really mean? We have created a small glossary.

AI / KI


Artificial Intelligence or AI, also known as Künstliche Intelligenz in German, refers to a subfield of computer science where computer programs simulate intelligent human behavior and decision-making structures. AI particularly focuses on machine learning. The term was originally coined by John McCarthy, an American computer scientist, who used it as the heading of a conference project proposal in 1956. The conference discussed, among other things, new programs capable of playing chess and checkers.

In Customer Insights, AI is used to enrich and analyze the merged data, including through machine learning.


Big Data

Coming from English, "big data" refers to a constantly evolving concept: it denotes a large volume of data that cannot be handled with traditional analysis and processing methods. The term also encompasses the new technologies that enable the processing of such vast amounts of data. Additionally, it signifies the societal transformation brought about by digitization and the increasing availability of data.

The term "big" in big data refers to the four dimensions of volume, velocity, variety, and veracity – that is, the scale of the data, the speed of data generation, the diversity of data types and sources, and the authenticity of the data.


Big Data Analytics


Big data analytics encompasses the processing, examination, and extraction of concrete information from enormous volumes of data. Its aim is to gain new insights. Big data analytics is employed by businesses to make more informed decisions and gain a competitive advantage. It is also utilized by government entities, such as in criminalistics, as well as by health authorities and medical research to predict epidemics, for example.


Business Intelligence (BI)


Business Intelligence, abbreviated as BI, is a term originating from business informatics that refers to the systematic analysis of companies' data to support business decision-making. Data is collected and evaluated through processes such as Customer Data Platforms. The deployment of BI aims to increase value creation and minimize costs, among other objectives.


Customer Data Platform (CPD) vs. Customer Relationship Management (CRM)


A Customer Data Platform (CDP) aids in the management of customer data, while Customer Relationship Management (CRM) helps in managing customer relationships. These two platforms are not mutually exclusive but are often used together to ensure efficient operations. In a Customer Data Platform, data related to customer behavior is collected, whereas CRM focuses on organizing and managing interactions between customers and teams. For instance, when using a customer service solution within a CRM, one can access customer contact information and their interaction history with the sales or support team. On the other hand, the data in a Customer Data Platform captures every step, from initial contact to transactions, social media responses, and online store behavior, enabling the creation of a unified profile. Customer Insights, for example, is a Customer Data Platform that can be used as a standalone product within the Power Platform, independent of CRM or Dynamics 365.


Machine Learning


Machine Learning refers to an artificial system that generates knowledge from experience. This "experience" can consist of examples provided during a learning phase, from which a model is built using algorithms based on patterns and regularities.


Profiling


Profiling involves creating a profile or comprehensive image of an individual, which can be used, for example, in job placement or criminalistics. Profiling entails the integration and analysis of various data sources.

From our podcast  INSIGHTS ON AIR (german):

How do you become a customer insights expert, Thomas?
Thomas Peschat from gorelate about the chicken and the egg, his development into a CI professional and the evaluation of Big Data.

In an interview with Theres Baumgartner, Thomas Peschat tells how he became a customer insights expert.

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