Anzeige
Erschienen in:
2018 | OriginalPaper | Buchkapitel
Examples of Measures in Measurement Systems
verfasst von : Miroslaw Staron, Wilhelm Meding
Erschienen in: Software Development Measurement Programs
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Never in history have we collected so much data as we have today; we have even coined an expression for this: “Big data.” Never have we measured and analyzed data as much as we do today. Data is easy to collect and store. Statistical methods and tools, business intelligence (BI) tools, and machine learning, together with cheap data storage and processing, make this possible. Everybody (well, almost) claims to be an expert in measuring. What we see, though, are evidences to the contrary. Companies and organizations are drawn in data and measures, while at the same time, measures are incomplete, misused, or not trusted. If there is one question we have heard over and over again it is “What should we measure?” It is a question asked by everyone, regardless of title, role and position in the organization’s hierarchy. In this chapter, we present a number of measures, how they “came to be,” and how to develop and visualize them. We present also a structured way to categorize measures, into five measurement areas.