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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

Learning how race conditions impact the transaction integrity of financial systems

Earlier in this chapter, we mentioned that PostgreSQL transactions have the ACID properties of atomicity, consistency, isolation, and durability. These qualities ensure that transactions are handled consistently and dependably. Let’s take a moment to discuss these in detail:

  • Atomicity: A database is said to be atomic when it needs the entire set of transactions to succeed for the changes to be reflected in the database. If one of the smaller operations fails, the entire operation will fail. But if all the tasks succeed, the entire operation will succeed and be reflected in the database.
  • Consistency: A database is consistent when the data adheres to the rules and relationships established in the database. Only changes that keep the data in a valid state should be made during a transaction. If the transaction is successful, it changes the database’s valid state to another. If...
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