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Managing Data Integrity for Finance

You're reading from   Managing Data Integrity for Finance Discover practical data quality management strategies for finance analysts and data professionals

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781837630141
Length 434 pages
Edition 1st Edition
Languages
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Author (1):
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Jane Sarah Lat Jane Sarah Lat
Author Profile Icon Jane Sarah Lat
Jane Sarah Lat
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Foundational Concepts for Data Quality and Data Integrity for Finance
2. Chapter 1: Recognizing the Importance of Data Integrity in Finance FREE CHAPTER 3. Chapter 2: Avoiding Common Data Integrity Issues and Challenges in Finance Teams 4. Chapter 3: Measuring the Impact of Data Integrity Issues 5. Part 2: Pragmatic Solutions to Manage Financial Data Quality and Data Integrity
6. Chapter 4: Understanding the Data Integrity Management Capabilities of Business Intelligence Tools 7. Chapter 5: Using Business Intelligence Tools to Fix Data Integrity Issues 8. Chapter 6: Implementing Best Practices When Using Business Intelligence Tools 9. Chapter 7: Detecting Fraudulent Transactions Affecting Financial Report Integrity 10. Part 3: Modern Strategies to Manage the Data Integrity of Finance Systems
11. Chapter 8: Using Database Locking Techniques for Financial Transaction Integrity 12. Chapter 9: Using Managed Ledger Databases for Finance Data Integrity 13. Chapter 10: Using Artificial Intelligence for Finance Data Quality Management 14. Index 15. 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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