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Data quality assurance is the process of data profiling to discover inconsistencies and other anomalies in the data, as well as performing data cleansing [17] [18] activities (e.g. removing outliers, missing data interpolation) to improve the data quality.
KPI information boards. A performance indicator or key performance indicator (KPI) is a type of performance measurement. [1] KPIs evaluate the success of an organization or of a particular activity (such as projects, programs, products and other initiatives) in which it engages. [2]
The GQM+Strategies approach was developed by Victor Basili and a group of researchers from the Fraunhofer Society. [10] It is based on the Goal Question Metric paradigm and adds the capability to create measurement programs that ensure alignment between business goals and strategies, software-specific goals, and measurement goals.
Select ingredients (metrics) of interest from each area when there are known objectives but want to save time. Use to refine existing program (rare), compare metrics vs. existing (completeness review) BI practitioner: Use for developing the calculations, finding the data needed to run the calculations, and building appropriate data structures
KPIs evaluate the success of an organization or of a particular activity (such as projects, programs, products and other initiatives) in which it engages. [22] KPIs provide a focus for strategic and operational improvement, create an analytical basis for decision making and help focus attention on what matters most.
A process-data diagram consists of two integrated models. The meta-process model on the left-hand side is based on a UML activity diagram, and the meta-data model on the right-hand side is an adapted UML class diagram. Combining these two models, the process-data diagram is used to reveal the relations between activities and artifacts (Saeki ...
Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [10] Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1]
The difficulty in ensuring data quality is integrating and reconciling data across different systems, and then deciding what subsets of data to make available. [3] Previously, analytics was considered a type of after-the-fact method of forecasting consumer behavior by examining the number of units sold in the last quarter or the last year. This ...