Book Image

Managing Data Integrity for Finance

By : Jane Sarah Lat
Book Image

Managing Data Integrity for Finance

By: Jane Sarah Lat

Overview of this book

Data integrity management plays a critical role in the success and effectiveness of organizations trying to use financial and operational data to make business decisions. Unfortunately, there is a big gap between the analysis and management of finance data along with the proper implementation of complex data systems across various organizations. The first part of this book covers the important concepts for data quality and data integrity relevant to finance, data, and tech professionals. The second part then focuses on having you use several data tools and platforms to manage and resolve data integrity issues on financial data. The last part of this the book covers intermediate and advanced solutions, including managed cloud-based ledger databases, database locks, and artificial intelligence, to manage the integrity of financial data in systems and databases. After finishing this hands-on book, you will be able to solve various data integrity issues experienced by organizations globally.
Table of Contents (16 chapters)
1
Part 1: Foundational Concepts for Data Quality and Data Integrity for Finance
5
Part 2: Pragmatic Solutions to Manage Financial Data Quality and Data Integrity
10
Part 3: Modern Strategies to Manage the Data Integrity of Finance Systems

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.

Here are the topics that...