Data integrity management plays a critical role in the success and effectiveness of organizations trying to use financial and operational data to make business decisions. Unfortunately, there is a big gap between the analysis and management of finance data along with the proper implementation of complex data systems across various organizations.
The first part of this book covers the important concepts for data quality and data integrity relevant to finance, data, and tech professionals. The second part then focuses on having you use several data tools and platforms to manage and resolve data integrity issues on financial data. The last part of this the book covers intermediate and advanced solutions, including managed cloud-based ledger databases, database locks, and artificial intelligence, to manage the integrity of financial data in systems and databases.
After finishing this hands-on book, you will be able to solve various data integrity issues experienced by organizations globally.
publication date
2024-01-31
what you will learn
Develop a customized financial data quality scorecard
Utilize business intelligence tools to detect, manage, and resolve data integrity issues
Find out how to use managed cloud-based ledger databases for financial data integrity
Apply database locking techniques to prevent transaction integrity issues involving finance data
Discover the methods to detect fraudulent transactions affecting financial report integrity
Use artificial intelligence-powered solutions to resolve various data integrity issues and challenges
key features
Accelerate data integrity management using artificial intelligence-powered solutions * Learn how business intelligence tools, ledger databases, and database locks solve data integrity issues * Find out how to detect fraudulent transactions affecting financial report integrity
approach
The book begins with the foundational concepts for data integrity relevant to finance domains. Next, it focuses on having the reader use several data tools and platforms to manage data integrity issues on sample finance data. Towards the end of the book, the book covers solutions including blockchain, database ledgers, and database locks to manage data integrity for transactional finance systems.
audience
This book is for financial analysts, technical leaders, and data professionals interested in learning practical strategies for managing data integrity and data quality using relevant frameworks and tools. A basic understanding of finance concepts, accounting, and data analysis is expected. Knowledge of finance management is not a prerequisite, but it’ll help you grasp the more advanced topics covered in this book.
short description
This hands-on guide will help you learn various strategies for managing data integrity and data quality using effective frameworks, tools, and strategies. Get ready to explore a range of methods and solutions for finance projects and requirements.
subtitle
Discover practical data quality management strategies for finance analysts and data professionals
keywords
Financial Management; Data Analysis; Financial Analysis; Portfolio management; Financial Reporting; Anomaly Detection; Credit score; Data Governance; Financial Data; financial analysis books
Product ISBN
9781837630141
