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

Handling data corruption and financial transaction data integrity issues in internal systems and databases

System-level data integrity and data corruption bugs can result in a wide range of issues, both minor and severe. A system failure or corrupted file may cause operational delays, decreased productivity, and missed deadlines. Additionally, such incidents may result in violations of data privacy laws and regulations, leading to costly fines and harm to a company’s reputation. Furthermore, errors in application development, such as improper data validation or input, may lead to unnoticed data integrity issues, which may cause inaccurate financial reporting, compromised decision-making, and potential legal consequences. Therefore, safeguarding data integrity must be a top priority for businesses, and strategies should be established to prevent and mitigate the risks of data corruption and related issues.

Note

Let’s talk about a popular example of how system-level...