Data management affects every department and diverse teams. But many terms in data & analytics are not self-explanatory, which makes communication difficult. Therefore, you will find in our "Data Knowledge" glossary definitions of the most relevant data management topics. Simple and to the point.
Data stocks in companies are growing every day - and thanks to technological progress, the opportunities to turn this data into added value are also increasing. More and more frequently, decisions are no longer made based on experience or gut feeling alone, but on the basis of data analysis tools. How valid such decisions are, however, depends on the quality of the data and thus also of the data management, which is an interdisciplinary task of management, specialist departments and IT administration.
For constructive discussions about data-related decisions, it is essential that all stakeholders share the same basic understanding of terms and processes. Therefore, we have compiled a collection of definitions, descriptions and comprehensible explanations of the most important terminology used in data management. The glossary supports professionals and managers in creating a common knowledge base. This ensures a purposeful and effective discussion in their digitization projects and data & analytics programs.
In addition to definitions of familiar industry terms, the glossary always offers a classification in the entrepreneurial context. What are the advantages or risks of the technology? What should companies look out for when implementing suitable software solutions? Some buzzwords such as single point of truth, master data or data integration are used quite naturally. But not everyone involved in a project may know exactly what is hidden behind these terms with the necessary granularity. Our articles close knowledge gaps and may even give you a head start or two.
Digital Asset Management
Single Point of Truth