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The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (Meta)data use vocabularies that follow FAIR principles I3.
Data requirements can also be identified in the contract via special contract clauses (e.g., DFARS), which define special data provisions such as rights in data, warranty, etc. SOW guidance of MIL-HDBK-245D describes the desired relationship: "Work requirements should be specified in the SOW, and all data requirements for delivery, format, and ...
BCBS 239 is the Basel Committee on Banking Supervision's standard number 239. The subject title of the standard is: "Principles for effective risk data aggregation and risk reporting".
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.
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
Compliance refers to the human-subject response to a proposed experimental treatment condition. Similar to the ATE, the LATE is calculated but does not include non-compliant parties. If the goal is to evaluate the effect of a treatment in ideal, compliant subjects, the LATE value will give a more precise estimate.
However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a recent phenomenon, the requirement for data to aid decision-making traces back to the early 1970s with the emergence of decision support systems (DSS).
Delivery schedule adherence (DSA) is a business metric used to calculate the timeliness of deliveries from suppliers. It is a commonly used supply chain metric and forms part of the Quality, Cost, Delivery group of performance indicators.