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2. Data quality - Wikipedia

   en.wikipedia.org/wiki/Data_quality

   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.

3. Data analysis - Wikipedia

   en.wikipedia.org/wiki/Data_analysis

   Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

4. Information quality - Wikipedia

   en.wikipedia.org/wiki/Information_quality

   Larry English prefers the term "characteristics" to dimensions. [6] In fact, a considerable amount of information quality research involves investigating and describing various categories of desirable attributes (or dimensions) of data. Research has recently shown the huge diversity of terms and classification structures used. [7]

5. ISO 8000 - Wikipedia

   en.wikipedia.org/wiki/ISO_8000

   ISO 8000 is the international standard for Data Quality and Enterprise Master Data.Widely adopted internationally [1] [2] [3] it describes the features and defines the requirements for standard exchange of Master Data among business partners.

6. Dimension (data warehouse) - Wikipedia

   en.wikipedia.org/wiki/Dimension_(data_warehouse)

   [1] [2] (Note: People and time sometimes are not modeled as dimensions.) In a data warehouse, dimensions provide structured labeling information to otherwise unordered numeric measures. The dimension is a data set composed of individual, non-overlapping data elements. The primary functions of dimensions are threefold: to provide filtering ...

7. OLAP cube - Wikipedia

   en.wikipedia.org/wiki/OLAP_cube

   For example, a company might wish to summarize financial data by product, by time-period, and by city to compare actual and budget expenses. Product, time, city and scenario (actual and budget) are the data's dimensions. [3] Cube is a shorthand for multidimensional dataset, given that data can have an arbitrary number of dimensions.

8. Eight dimensions of quality - Wikipedia

   en.wikipedia.org/wiki/Eight_dimensions_of_quality

   The dimension of conformance depicts to what extent a product’s design and operating characteristics meet established standards. This dimension owes the most to the traditional approaches to quality pioneered by experts like Juran. [6] Customers usually associate high quality with a product that exactly meets its requirements.

9. Seven basic tools of quality - Wikipedia

   en.wikipedia.org/wiki/Seven_Basic_Tools_of_Quality

   The seven basic tools of quality are a fixed set of visual exercises identified as being most helpful in troubleshooting issues related to quality. [1] They are called basic because they are suitable for people with little formal training in statistics and because they can be used to solve the vast majority of quality-related issues.