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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

Exploring the best practices when using ledger databases

In this chapter, we covered a lot of important concepts on how QLDB retains a comprehensive and verifiable record of modifications made over time. This capability enhances the ledger’s transparency and maintains its data integrity. In this section, we will look at the best practices when working with ledger databases. They are as follows:

  • Data structure: Implement a data structure that fits your needs. Organize and design the tables in a way that makes it easy to search for and retrieve data efficiently.
  • Immutability: Since QLDB is immutable and contains a verifiable history of all the changes, make use of this capability to maintain data integrity and traceability.
  • Querying: There are some constraints concerning querying the data in QLDB. These must be taken into consideration when writing queries for optimal performance.
  • Cost management: Make sure you have a good understanding of how QLDB pricing...
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