Measuring data quality for ongoing improvement [[electronic resource] ] : a data quality assessment framework / / Laura Sebastian-Coleman |
Autore | Sebastian-Coleman Laura (Data quality author and practitioner) |
Edizione | [1st edition] |
Pubbl/distr/stampa | Waltham, Mass., : Elsevier, 2013 |
Descrizione fisica | 1 online resource (404 p.) |
Disciplina | 005.7/3 |
Collana | The Morgan Kaufmann Series on Business Intelligence |
Soggetto topico |
Data structures (Computer science)
Databases - Quality control |
Soggetto genere / forma | Electronic books. |
ISBN |
1-283-93318-7
0-12-397754-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Measuring Data Quality for Ongoing Improvement; Copyright Page; Contents; Acknowledgments; Foreword; Author Biography; Data Quality Measurement: the Problem we are Trying to Solve; Introduction: Measuring Data Quality for Ongoing Improvement; Recurring Challenges in the Context of Data Quality; Definitions of Data Quality; Expectations about Data; Risks to Data; The Criticality of Metadata and Explicit Knowledge; The Business/Information Technology Divide; Data Quality Strategy; DQAF: the Data Quality Assessment Framework
Overview of Measuring Data Quality for Ongoing Improvement Section One: Concepts and Definitions; Section Two: DQAF Overview; Section Three: Data Assessment Scenarios; Section Four: Applying the DQAF to Data Requirements; Section Five: Data Quality Strategy; Section Six: the DQAF in Depth; Intended Audience; What Measuring Data Quality for Ongoing Improvement Does Not Do; Why I Wrote Measuring Data Quality for Ongoing Improvement; 1: Concepts and Definitions; 1 Data; Purpose; Data; Data as Representation; The Implications of Data's Semiotic Function; Semiotics and Data Quality; Data as Facts Data as a Product Data as Input to Analyses; Data and Expectations; Information; Concluding Thoughts; 2 Data, People, and Systems; Purpose; Enterprise or Organization; IT and the Business; Data Producers; Data Consumers; Data Brokers; Data Stewards and Data Stewardship; Data Owners; Data Ownership and Data Governance; IT, the Business, and Data Owners, Redux; Data Quality Program Team; Stakeholder; Systems and System Design; Concluding Thoughts; 3 Data Management, Models, and Metadata; Purpose; Data Management; Database, Data Warehouse, Data Asset, Dataset Source System, Target System, System of Record Data Models; Types of Data Models; Physical Characteristics of Data; Metadata; Metadata as Explicit Knowledge; Data Chain and Information Life Cycle; Data Lineage and Data Provenance; Concluding Thoughts; 4 Data Quality and Measurement; Purpose; Data Quality; Data Quality Dimensions; Measurement; Measurement as Data; Data Quality Measurement and the Business/IT Divide; Characteristics of Effective Measurements; Measurements must be Comprehensible and Interpretable; Measurements must be Reproducible; Measurements must be Purposeful Data Quality Assessment Data Quality Dimensions, DQAF Measurement Types, Specific Data Quality Metrics; Data Profiling; Data Quality Issues and Data Issue Management; Reasonability Checks; Data Quality Thresholds; Process Controls; In-line Data Quality Measurement and Monitoring; Concluding Thoughts; 2: DQAF Concepts and Measurement Types; 5 DQAF Concepts; Purpose; The Problem the DQAF Addresses; Data Quality Expectations and Data Management; The Scope of the DQAF; DQAF Quality Dimensions; Completeness; Timeliness; Validity; Consistency; Integrity; The Question of Accuracy Defining DQAF Measurement Types |
Record Nr. | UNINA-9910463018203321 |
Sebastian-Coleman Laura (Data quality author and practitioner) | ||
Waltham, Mass., : Elsevier, 2013 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Measuring data quality for ongoing improvement : a data quality assessment framework / / Laura Sebastian-Coleman |
Autore | Sebastian-Coleman Laura (Data quality author and practitioner) |
Edizione | [1st edition] |
Pubbl/distr/stampa | Waltham, Mass., : Elsevier, 2013 |
Descrizione fisica | 1 online resource (xxxix, 324, 39 pages) : color illustrations |
Disciplina | 005.7/3 |
Collana | The Morgan Kaufmann Series on Business Intelligence |
Soggetto topico |
Data structures (Computer science)
Databases - Quality control |
ISBN |
1-283-93318-7
0-12-397754-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Measuring Data Quality for Ongoing Improvement; Copyright Page; Contents; Acknowledgments; Foreword; Author Biography; Data Quality Measurement: the Problem we are Trying to Solve; Introduction: Measuring Data Quality for Ongoing Improvement; Recurring Challenges in the Context of Data Quality; Definitions of Data Quality; Expectations about Data; Risks to Data; The Criticality of Metadata and Explicit Knowledge; The Business/Information Technology Divide; Data Quality Strategy; DQAF: the Data Quality Assessment Framework
Overview of Measuring Data Quality for Ongoing Improvement Section One: Concepts and Definitions; Section Two: DQAF Overview; Section Three: Data Assessment Scenarios; Section Four: Applying the DQAF to Data Requirements; Section Five: Data Quality Strategy; Section Six: the DQAF in Depth; Intended Audience; What Measuring Data Quality for Ongoing Improvement Does Not Do; Why I Wrote Measuring Data Quality for Ongoing Improvement; 1: Concepts and Definitions; 1 Data; Purpose; Data; Data as Representation; The Implications of Data's Semiotic Function; Semiotics and Data Quality; Data as Facts Data as a Product Data as Input to Analyses; Data and Expectations; Information; Concluding Thoughts; 2 Data, People, and Systems; Purpose; Enterprise or Organization; IT and the Business; Data Producers; Data Consumers; Data Brokers; Data Stewards and Data Stewardship; Data Owners; Data Ownership and Data Governance; IT, the Business, and Data Owners, Redux; Data Quality Program Team; Stakeholder; Systems and System Design; Concluding Thoughts; 3 Data Management, Models, and Metadata; Purpose; Data Management; Database, Data Warehouse, Data Asset, Dataset Source System, Target System, System of Record Data Models; Types of Data Models; Physical Characteristics of Data; Metadata; Metadata as Explicit Knowledge; Data Chain and Information Life Cycle; Data Lineage and Data Provenance; Concluding Thoughts; 4 Data Quality and Measurement; Purpose; Data Quality; Data Quality Dimensions; Measurement; Measurement as Data; Data Quality Measurement and the Business/IT Divide; Characteristics of Effective Measurements; Measurements must be Comprehensible and Interpretable; Measurements must be Reproducible; Measurements must be Purposeful Data Quality Assessment Data Quality Dimensions, DQAF Measurement Types, Specific Data Quality Metrics; Data Profiling; Data Quality Issues and Data Issue Management; Reasonability Checks; Data Quality Thresholds; Process Controls; In-line Data Quality Measurement and Monitoring; Concluding Thoughts; 2: DQAF Concepts and Measurement Types; 5 DQAF Concepts; Purpose; The Problem the DQAF Addresses; Data Quality Expectations and Data Management; The Scope of the DQAF; DQAF Quality Dimensions; Completeness; Timeliness; Validity; Consistency; Integrity; The Question of Accuracy Defining DQAF Measurement Types |
Record Nr. | UNINA-9910786101103321 |
Sebastian-Coleman Laura (Data quality author and practitioner) | ||
Waltham, Mass., : Elsevier, 2013 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Measuring data quality for ongoing improvement : a data quality assessment framework / / Laura Sebastian-Coleman |
Autore | Sebastian-Coleman Laura (Data quality author and practitioner) |
Edizione | [1st edition] |
Pubbl/distr/stampa | Waltham, Mass., : Elsevier, 2013 |
Descrizione fisica | 1 online resource (xxxix, 324, 39 pages) : color illustrations |
Disciplina | 005.7/3 |
Collana | The Morgan Kaufmann Series on Business Intelligence |
Soggetto topico |
Data structures (Computer science)
Databases - Quality control |
ISBN |
1-283-93318-7
0-12-397754-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Measuring Data Quality for Ongoing Improvement; Copyright Page; Contents; Acknowledgments; Foreword; Author Biography; Data Quality Measurement: the Problem we are Trying to Solve; Introduction: Measuring Data Quality for Ongoing Improvement; Recurring Challenges in the Context of Data Quality; Definitions of Data Quality; Expectations about Data; Risks to Data; The Criticality of Metadata and Explicit Knowledge; The Business/Information Technology Divide; Data Quality Strategy; DQAF: the Data Quality Assessment Framework
Overview of Measuring Data Quality for Ongoing Improvement Section One: Concepts and Definitions; Section Two: DQAF Overview; Section Three: Data Assessment Scenarios; Section Four: Applying the DQAF to Data Requirements; Section Five: Data Quality Strategy; Section Six: the DQAF in Depth; Intended Audience; What Measuring Data Quality for Ongoing Improvement Does Not Do; Why I Wrote Measuring Data Quality for Ongoing Improvement; 1: Concepts and Definitions; 1 Data; Purpose; Data; Data as Representation; The Implications of Data's Semiotic Function; Semiotics and Data Quality; Data as Facts Data as a Product Data as Input to Analyses; Data and Expectations; Information; Concluding Thoughts; 2 Data, People, and Systems; Purpose; Enterprise or Organization; IT and the Business; Data Producers; Data Consumers; Data Brokers; Data Stewards and Data Stewardship; Data Owners; Data Ownership and Data Governance; IT, the Business, and Data Owners, Redux; Data Quality Program Team; Stakeholder; Systems and System Design; Concluding Thoughts; 3 Data Management, Models, and Metadata; Purpose; Data Management; Database, Data Warehouse, Data Asset, Dataset Source System, Target System, System of Record Data Models; Types of Data Models; Physical Characteristics of Data; Metadata; Metadata as Explicit Knowledge; Data Chain and Information Life Cycle; Data Lineage and Data Provenance; Concluding Thoughts; 4 Data Quality and Measurement; Purpose; Data Quality; Data Quality Dimensions; Measurement; Measurement as Data; Data Quality Measurement and the Business/IT Divide; Characteristics of Effective Measurements; Measurements must be Comprehensible and Interpretable; Measurements must be Reproducible; Measurements must be Purposeful Data Quality Assessment Data Quality Dimensions, DQAF Measurement Types, Specific Data Quality Metrics; Data Profiling; Data Quality Issues and Data Issue Management; Reasonability Checks; Data Quality Thresholds; Process Controls; In-line Data Quality Measurement and Monitoring; Concluding Thoughts; 2: DQAF Concepts and Measurement Types; 5 DQAF Concepts; Purpose; The Problem the DQAF Addresses; Data Quality Expectations and Data Management; The Scope of the DQAF; DQAF Quality Dimensions; Completeness; Timeliness; Validity; Consistency; Integrity; The Question of Accuracy Defining DQAF Measurement Types |
Record Nr. | UNINA-9910810784503321 |
Sebastian-Coleman Laura (Data quality author and practitioner) | ||
Waltham, Mass., : Elsevier, 2013 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|