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Managing Data Integrity for Finance

You're reading from  Managing Data Integrity for Finance

Product type Book
Published in Jan 2024
Publisher Packt
ISBN-13 9781837630141
Pages 434 pages
Edition 1st Edition
Languages
Author (1):
Jane Sarah Lat Jane Sarah Lat
Profile icon Jane Sarah Lat

Table of Contents (16) Chapters

Preface Part 1: Foundational Concepts for Data Quality and Data Integrity for Finance
Chapter 1: Recognizing the Importance of Data Integrity in Finance Chapter 2: Avoiding Common Data Integrity Issues and Challenges in Finance Teams Chapter 3: Measuring the Impact of Data Integrity Issues Part 2: Pragmatic Solutions to Manage Financial Data Quality and Data Integrity
Chapter 4: Understanding the Data Integrity Management Capabilities of Business Intelligence Tools Chapter 5: Using Business Intelligence Tools to Fix Data Integrity Issues Chapter 6: Implementing Best Practices When Using Business Intelligence Tools Chapter 7: Detecting Fraudulent Transactions Affecting Financial Report Integrity Part 3: Modern Strategies to Manage the Data Integrity of Finance Systems
Chapter 8: Using Database Locking Techniques for Financial Transaction Integrity Chapter 9: Using Managed Ledger Databases for Finance Data Integrity Chapter 10: Using Artificial Intelligence for Finance Data Quality Management Index Other Books You May Enjoy

Reviewing how database locks prevent financial transaction integrity issues

Database locks are essential for maintaining the integrity of financial transactions. They play a critical role in preventing conflicts and ensuring that concurrent access to data remains consistent. By controlling the simultaneous modification of shared resources, such as records or tables, locks ensure that transactions have exclusive access to the records they need (and ensure that the numbers add up correctly!). This helps maintain the accuracy and reliability of financial data by preventing data inconsistencies and conflicts.

Let’s go back to the table we created earlier, as shown in Figure 8.26. For instance, we need to update the price of the ticket for Conference X and add $10. A price increase of $10 is added depending on the demand:

Figure 8.26 – Current ticket prices

Figure 8.26 – Current ticket prices

If only one person is making the change to the database, there would be no problem....

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