Managing Data Integrity for Finance: Practical data quality management strategies for finance analysts and data professionals

di Jane Sarah Lat (Autore)

Packt Publishing Limited, 2024

Level up your career by learning the best practices for managing data quality and integrity of your financial data Key Features Understand the financial data quality metrics available to measure the quality of finance data Perform data quality management operations using a variety of data tools for finance Learn how ledger databases, database locks, and machine learning solve data integrity challenges Book DescriptionThere is a big gap between the finance and technology sectors when it comes to the proper analysis and management of finance data and the proper implementation of data systems. More companies around the world have been using finance and operational data to make business decisions. That said, data quality and data integrity play a crucial role in the success and effectiveness of those organizations. The first part covers the foundational concepts for data quality and data integrity relevant to finance domains such as banking, insurance, portfolio management, credit and risk management, and corporate finance. The second part focuses on having the reader use several data tools and platforms to manage data quality and data integrity issues on sample finance data. Finally, the book covers intermediate and advanced solutions including blockchain solutions, database ledgers, and database locks to manage data integrity for transactional finance systems. After finishing this hands-on book, you will be able to recommend various finance and technical solutions to solve transaction and data integrity challenges experienced by finance organizations.What you will learn Develop data quality metrics to measure data integrity Perform finance data quality management operations using data tools Discover how ledger databases help prevent data integrity issues Apply database techniques to prevent transaction data integrity issues Use machine learning methods to manage data integrity Implement data quality initiatives for financial projects Handle missing financial reporting data using Generative AI Implement best practices using Generative AI in Data Quality Management Who this book is forThis book is intended for financial analysts, technical leaders, and data professionals interested in learning practical strategies for managing data integrity and data quality using relevant frameworks, tools, and strategies. The reader is expected to have a basic understanding of finance concepts, accounting, and data analysis. Basic knowledge of finance management is not required but will help grasp the intermediate topics of the book.

• Autore: Jane Sarah Lat
• Editore: Packt Publishing Limited
• Anno: 2024
• Rilegatura: Paperback / softback
• Pagine: 434 p.
• Dimensioni: 235 x 191 mm
• EAN: 9781837630141

Testo in English