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The Data Quality Blueprint: A Comprehensive Step by Step Guide to an Effective & Long Lasting Enterprise-Wide Data Quality Solution (en Inglés)
John Parkinson (Autor)
·
Holifast Limited
· Tapa Dura
The Data Quality Blueprint: A Comprehensive Step by Step Guide to an Effective & Long Lasting Enterprise-Wide Data Quality Solution (en Inglés) - John Parkinson
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Reseña del libro "The Data Quality Blueprint: A Comprehensive Step by Step Guide to an Effective & Long Lasting Enterprise-Wide Data Quality Solution (en Inglés)"
Most organisations face data quality problems, a legacy of many years of poor information management. With increasing regulation and increasing competition it is no longer an option to simply ignore these problems. With the cost of poor data quality often approaching 30% of turnover, it is a problem worth solving. Few organisations have succeeded. A common scenario is to spend vast effort remediating data only to see it degrade again in a short period of time. John Parkinson has worked for 20 years in the information management industry and on many large data quality remediation projects. His experience has shown that organisations fail to consider the organisation as a holistic unit, and miss out key elements of the solution by focusing only on the data itself. The conclusion is they also need to focus on the processes and architecture that create and maintain it. However knowing this does not make it happen in reality. Drawing on both his project management experience and also his data quality, data strategy, data governance and data management experience, John has developed a clear practical blueprint that organisations can use to create a long lasting data quality solution. This book includes everything a data quality practitioner needs. It covers: Why organisations should care about poor data quality. How to assess data quality, and determine the impact on the organisation. How to win the hearts and minds of the organisation. How to develop information requirements, a data strategy and data quality strategies. How to create data quality dashboards and define metrics. How to perform discovery work across the organisation. How to perform remediation planning and design, and how to approach the remediation itself. How to embed data quality in the organisation, including governance, training and knowledge management. A practical consideration of data quality in projects This book is truly a one-stop-shop for data quality in the enterprise.
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