Spatial Data Quality Management in ArcGIS Pro
Language: English
Published by Independently published, 2025
- Softcover
- New
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- Title
- Spatial Data Quality Management in ArcGIS Pro
- Author
- Nofal, د Rasha Saber Nofal AbedElkawy; Abbas, م Ahmed Mahmoued
- Publisher
- Independently published
- Publication year
- 2025
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798306850665
The book "Spatial Data Quality Management in ArcGIS Pro" serves as a comprehensive reference for anyone seeking to enhance the quality and analysis of spatial data effectively using ArcGIS Pro.
Spatial data quality is the backbone of any project that relies on Geographic Information Systems (GIS). Decisions based on low-quality data can often be inaccurate or misleading. This book provides the tools and methods necessary to ensure data accuracy and validity through a comprehensive approach that covers all aspects of spatial quality management.
The book comprises six chapters, preceded by an introduction:
1. Chapter One explores Data Engineering, focusing on the foundations of metadata.
2. Chapter Two covers Data Quality Control Using Topology Rules.
3. Chapter Three delves into managing geospatial data through Attribute Rules, including calculation, constraint, and validation rules.
4. Chapter Four discusses Data Quality Management Using Data Reviewer, highlighting how to run batch jobs, manage errors, and generate reports.
5. Chapter Five offers a simplified explanation of Attribute Rules, while showcasing the use of AI tools such as ChatGPT to enhance data quality and simplify coding tasks.
6. The final chapter introduces the basics of ArcGIS Arcade, laying a scientific foundation for readers to better understand the rules used to ensure data quality.
This book is designed to guide readers through practical and theoretical aspects, enabling them to effectively manage spatial data quality while leveraging advanced tools and methodologies.
Spatial data quality is the backbone of any project that relies on Geographic Information Systems (GIS). Decisions based on low-quality data can often be inaccurate or misleading. This book provides the tools and methods necessary to ensure data accuracy and validity through a comprehensive approach that covers all aspects of spatial quality management.
The book comprises six chapters, preceded by an introduction:
1. Chapter One explores Data Engineering, focusing on the foundations of metadata.
2. Chapter Two covers Data Quality Control Using Topology Rules.
3. Chapter Three delves into managing geospatial data through Attribute Rules, including calculation, constraint, and validation rules.
4. Chapter Four discusses Data Quality Management Using Data Reviewer, highlighting how to run batch jobs, manage errors, and generate reports.
5. Chapter Five offers a simplified explanation of Attribute Rules, while showcasing the use of AI tools such as ChatGPT to enhance data quality and simplify coding tasks.
6. The final chapter introduces the basics of ArcGIS Arcade, laying a scientific foundation for readers to better understand the rules used to ensure data quality.
This book is designed to guide readers through practical and theoretical aspects, enabling them to effectively manage spatial data quality while leveraging advanced tools and methodologies.
"Synopsis" may belong to another edition of this title.
Ria Christie Collections
Uxbridge, United Kingdom
5-star seller
AbeBooks seller since March 25, 2015
Shipping rates from United Kingdom to U.S.A.
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