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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

Using Database Locking Techniques for Financial Transaction Integrity

In Chapter 1, Recognizing the Importance of Data Integrity in Finance, we discussed how locking techniques such as mutual exclusion locks can help maintain the integrity of transactions and financial data. These locking techniques (as well as the database constraints discussed in Chapter 2, Avoiding Common Data Integrity Issues and Challenges in Finance Teams) help ensure that financial numbers and transaction values add up, even if simultaneous actions or operations are happening at the same time. In this chapter, we’ll build on top of what we learned in the previous chapters and dive deeper into how race conditions can affect financial transaction integrity in databases and how these race conditions can be handled properly. This chapter will offer practical guidance on using specific SQL and database techniques to prevent transaction data integrity inconsistencies and issues.

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