12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Data discovery is a form of data analysis in which data from various sources is collected, analyzed and visualized to uncover and understand business information. The goal is to gain insights into the data that can be useful for decisions and processes within an organization. Data discovery tools can help companies better understand how to use data and improve decision making.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
A data warehouse architecture is a technical system that provides a consistent and integrated database for analysis and reporting. It is a central data repository where data from multiple sources is collected, consolidated, and stored for analysis and reporting. A data warehouse architecture can contain multiple components, including a database, ETL processes, data integration, data quality processes, reporting, and analytics.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Competitor analysis is a method of strategic planning in which companies identify, evaluate, and compare the products, services, and strategies of their competitors. It is an important analysis method that helps companies identify the strengths and weaknesses of their competitors in order to be better prepared to face them.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Competitive analysis is a strategic tool that allows companies to monitor, understand and predict the competition in their market. It helps companies identify competitive advantages and strategies by evaluating their competitors in terms of products, prices, marketing strategies, financial strength, and other factors. This enables companies to make better decisions to achieve their strategic goals.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
In statistics, a variable is a characteristic of a target group that is used for analysis. A variable can be both a qualitative (e.g. gender) and a quantitative (e.g. age) characteristic of a target group. Variables can then be related to each other in order to make a specific statement about a target group.