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 data visualization to identify data outliers

Visualizations enable business professionals and companies to make sense of the numbers and deliver insights. They also make it easier to spot data outliers, as we will see in this section. Identifying outliers is important since they can significantly affect how you interpret the data and what actions you take. We can ask, Is this data point correct?, Is there insight from this?, or Could this be a potentially fraudulent transaction? In this section, we will visualize data outliers using Microsoft Power BI and Tableau through a scatter chart and a histogram.

Continuing our example from Chapter 5, Using Business Intelligence Tools to Fix Data Integrity Issues, about column distribution, let’s further analyze the dataset for 2020_Transactions.xlsx and review the sales quantity.

Figure 6.6 – Information about the column statistics and value distribution of the column

Figure 6.6 – Information about the column statistics and value distribution of the column

When we select the Quantity...