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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

Handling confusing date convention formats

One of the most common data integrity issues encountered when dealing with date time values involves the inconsistent positioning of the month and date values in data entries and transactions. In some countries, mm/dd/yyyy is used for the date format. In other countries, dd/mm/yyyy is used. Of course, the number of days (that is, 01 to 31) exceeds the number of months (that is, 01 to 12). However, what if the record stored in the sheet or database is 03/06/1990? If the assumed format is mm/dd/yyyy, then 03/06/1990 will be interpreted as March 6, 1990. On the other hand, if the assumed format is dd/mm/yyyy, then the same date will be interpreted as June 3, 1990 instead.

Now, we have a data integrity issue when a single column involves both formats. There are a variety of reasons this could happen and one of the possible causes is if records from multiple data sources were merged into a single sheet or table without taking into account the...

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