Data Quality Assessment - Practical Skills
Co říká o významu Data Quality jeden ze špičkových odborníků a author knihy "Data Quality Assessment book" Arkady Maydanchik:
"Data quality management is one of the fastest growing areas of information technology. According to the experts the cost of poor data quality can reach as high as 15 to 25% of operating profit. Corporations are losing millions of dollars due to inaccurate data. Yet data quality profession is still in its infancy and few experts offer comprehensive methodology and practical solutions to the problem."
Portál "Data Quality Group" nabízí řadu kurzů zaměřených na Data Quality.
Pohled do podrobného programu jednoho z kurzů může být velmi poučný pro upřesnění představy o nové disciplině.
Název kurzu je: "Data Quality Assessment - Practical Skills".
Komu je kurz určen: Data quality practitioners - those in the trenches who are responsible to manage, maintain, and deliver high-quality data and to continuously improve the quality of data.
Co se naučíte:
- The what, why, when, and how of data quality assessment.
- How to identify and use data quality rules.
- How to ensure completeness of data quality assessment.
- How to construct and use a data quality scorecard.
- How to collect, manage, maintain, warehouse and use data quality metadata.
Souhrn obsahu kurzu:
"More and more companies initiate data quality programs and form data stewardship groups everyyear. The starting point for any such program must be data quality assessment. Yet in absence of a comprehensive methodology, measuring data quality remains an elusive concept. It proves to be easier to produce hundreds or thousands of data error reports than to make any sense of them.This course gives comprehensive treatment to the process and practical challenges of data quality assessment. It starts with systematic treatment of various data quality rules and proceeds to the results analysis and building aggregated data quality scorecard. Special attention is paid to the architecture and functionality of the data quality metadata warehouse."
Základní osnova kurzu:
1. Introduction to Data Quality Assessment
2. Using Data Quality Rules for Data Quality Assessment
3. Ensuring Comprehensive Assessment
4. Constructing Data Quality Scorecard
5. Building Data Quality Metadata Warehouse
Podrobný program kurzu najdete na TÉTO adrese.
"Data quality management is one of the fastest growing areas of information technology. According to the experts the cost of poor data quality can reach as high as 15 to 25% of operating profit. Corporations are losing millions of dollars due to inaccurate data. Yet data quality profession is still in its infancy and few experts offer comprehensive methodology and practical solutions to the problem."
Portál "Data Quality Group" nabízí řadu kurzů zaměřených na Data Quality.
Pohled do podrobného programu jednoho z kurzů může být velmi poučný pro upřesnění představy o nové disciplině.
Název kurzu je: "Data Quality Assessment - Practical Skills".
Komu je kurz určen: Data quality practitioners - those in the trenches who are responsible to manage, maintain, and deliver high-quality data and to continuously improve the quality of data.
Co se naučíte:
- The what, why, when, and how of data quality assessment.
- How to identify and use data quality rules.
- How to ensure completeness of data quality assessment.
- How to construct and use a data quality scorecard.
- How to collect, manage, maintain, warehouse and use data quality metadata.
Souhrn obsahu kurzu:
"More and more companies initiate data quality programs and form data stewardship groups everyyear. The starting point for any such program must be data quality assessment. Yet in absence of a comprehensive methodology, measuring data quality remains an elusive concept. It proves to be easier to produce hundreds or thousands of data error reports than to make any sense of them.This course gives comprehensive treatment to the process and practical challenges of data quality assessment. It starts with systematic treatment of various data quality rules and proceeds to the results analysis and building aggregated data quality scorecard. Special attention is paid to the architecture and functionality of the data quality metadata warehouse."
Základní osnova kurzu:
1. Introduction to Data Quality Assessment
2. Using Data Quality Rules for Data Quality Assessment
3. Ensuring Comprehensive Assessment
4. Constructing Data Quality Scorecard
5. Building Data Quality Metadata Warehouse
Podrobný program kurzu najdete na TÉTO adrese.
vystavil doc. Arnošt Katolický | 19:12
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