Resources
Blogs
Mitigating Investigation Risks: The Essential Role of Data Profiling and Cleansing
In 2024, National Public Data, a prominent background check and fraud prevention service, made headlines for all the wrong reasons. Over 2.7 billion records containing
Why Data Quality Is the Foundation of Effective Compliance in Security and Investigations?
Imagine a fortress where every brick represents a piece of your organization’s data. Now, picture some bricks riddled with cracks and inconsistencies. Despite its imposing
How Data Deduplication Streamlines Investigations and Reduces Risk
In a survey conducted by Validity, 44% of the respondents revealed that duplicate data significantly impacted their ability to fully leverage their CRM systems. Now,
Mastering Data Integrity: How Record Linkage Can Transform Security and Investigations
With data breaches exposing more than eight million records worldwide just within the last quarter of 2023, an average data breach costing around USD 4.45
12 Challenges in Financial Data Migration and How IT leaders Tackle Them
12 Challenges in Financial Data Migration and How IT leaders Tackle Them Data migration projects are notorious for either going over budget or failing to
The Impact of Data Quality on Financial System Upgrades
The Impact of Data Quality on Financial System Upgrades Imagine losing 31% of your revenue due to poor data quality. For financial services, this isn’t
Data Integrity During System Transitions: 5 Key Tactics for Finance Leaders
Data Integrity During System Transitions: 5 Key Tactics for Finance Leaders So you are planning to migrate data to new systems, what could possibly go
5 Best Practices for Successful Data Migration in Financial Services
5 Best Practices for Successful Data Migration in Financial Services In 2022, Morgan Stanely was fined $35 million by the SEC for failing to protect
Top Strategies for Effectively Combining Data from Different Tables and Fine-Tuning Results
Combining data from different tables is crucial for accurate analytics. This article covers strategies for effectively combining data from different tables, from SQL joins to
Perfecting Data Matching: Essential Techniques and Best Practices Revealed
Duplicate records in a company’s datasets cause serious roadblocks to business success. 92% of organizations claim to suffer from the nightmare of data duplication. Nowadays,
Guide to data survivorship: How to build the golden record?
92% of organizations claim that their data sources are full of duplicate records. To make things worse, valuable information is present in every duplicate that
Standard Address Format: Address Standardization Guide – What, Why, and How?
Inaccurate and incomplete address data can cause your mail deliveries to be returned. In fact, the US postal service handled 6.5 billion pieces of UAA
Mastering Data Management for Data Matching: Key Features and Requirements for Building an Effective Data Catalog
Data matching helps ensure that disparate data sources are accurately aligned, cleansed, and ready for use. And that’s where an effective data catalog becomes essential
Advanced Data Clean and Match Techniques: A Comparative Review of Data Ladder vs. WinPure
Data cleaning and matching are critical processes for maintaining data integrity and deriving actionable insights from large datasets. This review dives into the advanced techniques
What is data integrity and how can you maintain it?
While surveying 2,190 global senior executives, only 35% claimed that they trust their organization’s data and analytics. As data usage surges across various business functions,
How to improve data quality: Define, design, and deliver
Today, data is no doubt one of the biggest assets of an organization. It is used everywhere – from a company’s day-to-day operations to its
Guide to pattern matching: What it means and how to do it?
Finding patterns is easy in any kind of data-rich environment; that’s what mediocre gamblers do. The key is in determining whether the patterns represent signal
Data Standardization Guide: Types, Benefits, and Process
Poor data standardization is a hidden profit killer. When customer names, products, or sales figures appear in different formats across systems (and often even within