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

Implementing Best Practices When Using Business Intelligence Tools

In the previous chapter, we learned how to use business intelligence (BI) tools to fix data integrity issues. We also covered the various data profiling features available and how to remove empty cells, remove duplicates, manage relationships in data models, identify data outliers, and deal with large financial datasets using data validation.

In this chapter, we will discuss the best practices when using Power BI Desktop, Tableau, and Alteryx Designer for data quality and integrity. By the end of this chapter, you will have a better understanding of how to leverage best practices when using these BI tools to ensure data integrity in finance.

We’ll cover the following in this chapter:

  • Handling confusing date convention formats
  • Using data visualization to identify data outliers
  • Managing orphaned records

By the end of this chapter, you will have a deeper understanding of what these BI...