Open AccessDigital Transformation: From Data Analytics to Customer Solutions. A Framework of Types, Techniques and Tools
Author(s) -
Michail Angelopoulos,
Yannis A. Pollalis
Publication year - 2021
Publication title -
archives of business research
Language(s) - English
Resource type - Journals
ISSN - 2054-7404
DOI - 10.14738/abr.96.10291
Subject(s) - computer science , data science , digital transformation , python (programming language) , analytics , business analytics , data analysis , data transformation , raw data , visualization , business model , data mining , data warehouse , world wide web , business analysis , marketing , business , programming language , operating system
It has become clear by now that the digital transformation has an obvious, lasting impact as much on the economic systems and commercial players as on the lives of individuals and on society at large. The decisions we make, our actions, even our existence in the digital world result in the production of massive amounts of data. These data can be integrated into large data analysis ecosystems and contribute positively to the revision of current business models and practices. Machine learning algorithms combined with the suitable tools, such as Python, turn raw data into useful information and lead to critical and correct decisions. The aim of this paper is to present a review of current popular and useful data analytics techniques and tools that lead to custom solutions for both customer and business. The most famous techniques based on Machine learning and visualization tools are represented here.