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Managing Data Integrity for Finance

Managing Data Integrity for Finance

By : Jane Sarah Lat
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Managing Data Integrity for Finance

Managing Data Integrity for Finance

5 (4)
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)
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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

Getting started with SQL

In Chapter 5, Using Business Intelligence Tools to Fix Data Integrity Issues, we worked with spreadsheets to manage and organize data. Spreadsheets can be used to perform various calculations, data processing, and basic data storage operations. However, there are other ways to store and manage information, especially when the data grows in volume. For one, we can make use of databases, which are specialized systems designed to store, retrieve, and manage vast amounts of structured data. They offer a structured framework with clear linkages between data tables, facilitating more effective data management and querying.

Structured Query Language (SQL) is a programming language that’s used to manage relational databases. Two of the most popular types of relational databases are MySQL and PostgreSQL. MySQL, which was developed by Oracle, is the most widely used relational database management system. In this chapter, we will be using PostgreSQL, which is...

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