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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

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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