Data Quality by Richard Y. Wang, Mostapha Ziad, Yang W. Lee (auth.)

By Richard Y. Wang, Mostapha Ziad, Yang W. Lee (auth.)

Data Quality presents an exposé of analysis and perform within the info caliber box for technically orientated readers. it really is in accordance with the study carried out on the MIT overall info caliber administration (TDQM) software and paintings from different best study associations. This publication is meant essentially for researchers, practitioners, educators and graduate scholars within the fields of computing device technological know-how, info know-how, and different interdisciplinary parts. It varieties a theoretical beginning that's either rigorous and suitable for facing complex matters concerning facts caliber. Written with the objective to supply an summary of the cumulated study effects from the MIT TDQM examine standpoint because it pertains to database learn, this e-book is a superb creation to Ph.D. who desire to additional pursue their learn within the information caliber sector. it's also a very good theoretical creation to IT pros who desire to achieve perception into theoretical ends up in the technically-oriented info caliber quarter, and practice a few of the key innovations to their practice.

Show description

Read or Download Data Quality PDF

Similar management information systems books

Integrated Information Management: Applying Successful Industrial Concepts in IT (Business Engineering)

This booklet addresses the demanding situations dealing with info administration (IM) and offers sensible resolution propositions. the 1st part describes six present tendencies and demanding situations to IM. the second one part introduces a complete version of built-in details administration (IIM). The 3rd part, utilizing six useful examples, describes how chosen thoughts of IIM could be carried out.

Homeland Security Preparedness and Information Systems: Strategies for Managing Public Policy

Place of origin safety info platforms are a huge sector of inquiry as a result large impression info structures play at the coaching and reaction of presidency to a terrorist assault or average catastrophe. place of birth protection Preparedness and data platforms: suggestions for dealing with Public coverage delves into the problems and demanding situations that public managers face within the adoption and implementation of data platforms for native land safeguard.

Active Knowledge Modeling of Enterprises

Company Modeling has been outlined because the paintings of externalizing firm wisdom, i. e. , representing the center wisdom of the firm. even though valuable in product layout and platforms improvement, for modeling and model-based methods to have a extra profound influence, a shift in modeling ways and methodologies is critical.

Additional resources for Data Quality

Sample text

Following the constructs developed in the relational model, a domain is defined as a set of values of similar type. Let ID be the domain for a system-wide unique identifier. Let D be a domain for an attribute. Let DID be defined on the Cartesian product D X ID. Let id be a quality key value associated with an attribute value d where d ∈D and id ∈ID. A quality relation (qr) of degree m is defined on the m+1 domains if it is a subset ofthe Cartesian product: ID X DID, X DID2 X ... X DIDm. Let qt be a quality tuple, which is an element in a quality relation.

One may want to know what standards a course has. This is an application quality requirement. An example of a data quality requirement is the accuracy of the class attendance data. There are various reasons why the three types of requirements are separated. First, quality requirements (both application quality and data quality requirements) differ from application requirements. Since they are often overlooked, this forces the user to identify them specifically during requirements analysis. Second, most existing systems were not built with quality requirements in mind.

Cartesian product If p1 and p2 are two polygen relations, then (p1 x p2 ) = {t1 o t2 | t1 ∈ p1 and t2 ∈ p2, where o denotes concatenation}. Restriction If p is a polygen relation, x ∈ attrs(p), y ∈ attrs(p), and θ is a binary relation, then p[x θ y]={t'|t'〈d〉=t〈d〉, t'〈o〉=t〈o〉, t'[w] 〈i〉 ∪ t[x] 〈o〉 ∪ t[y] 〈o〉 ∀ w ∈ attrs(p), 24 Extending the Relational Model to Capture Data Quality Attributes IF t ∈ p Chapter 2 t[x] 〈d〉 θ t[y]〈d〉}. Union If p1 and p2 are two polygen relations of degree n, t1 ∈p1, and t2 ∈p2, then (p1 ∪ p2) = {t'|t'=t1 IF t1〈d〉 ∈ p1 t1〈d〉 ∉ p2; t'=t2 IF t2〈d〉 ∉ p1 t2〈d〉 ∈ p2; t'〈d〉 = t1〈d〉, t'〈o〉 = t1〈o〉 t2〈o〉, t'〈i〉 ∪ t2〈i〉 if t1〈d〉 = t2〈d〉} Difference Let p〈o〉 denote the union of all the t〈o〉 sets in p, and p〈i〉 denote the union of all the t〈i〉 sets in p.

Download PDF sample

Rated 4.53 of 5 – based on 43 votes