Resources
Blogs
How Data Deduplication Streamlines Investigations and Reduces Risk
Last Updated on January 1, 2026 In a survey conducted by Validity, 44% of the respondents revealed that duplicate data significantly impacted their ability
Mastering Data Integrity: How Record Linkage Can Transform Security and Investigations
Last Updated on January 1, 2026 With data breaches exposing more than eight million records worldwide just within the last quarter of 2023, an
12 Challenges in Financial Data Migration and How IT leaders Tackle Them
Last Updated on January 7, 2026 Data migration projects are notorious for either going over budget or failing to meet their original objectives. While
The Impact of Data Quality on Financial System Upgrades
Last Updated on January 7, 2026 Imagine losing 31% of your revenue due to poor data quality. For financial services, this isn’t just hypothetical
Data Integrity During System Transitions: 5 Key Tactics for Finance Leaders
Last Updated on January 7, 2026 So you are planning to migrate data to new systems, what could possibly go wrong? As it turns
5 Best Practices for Successful Data Migration in Financial Services
Last Updated on January 8, 2026 In 2022, Morgan Stanely was fined $35 million by the SEC for failing to protect customer data. This
Top Strategies for Effectively Combining Data from Different Tables and Fine-Tuning Results
Last Updated on February 4, 2026 Combining data from different tables is crucial for accurate analytics. This article covers strategies for effectively combining data
Perfecting Data Matching: A Practical Guide for Creating Reliable, Connected Data
Last Updated on February 16, 2026 Summary: Data matching connects records that belong to the same entity across different systems, formats, and datasets. This
Guide to data survivorship: How to build the golden record?
Last Updated on February 16, 2026 92% of organizations claim that their data sources are full of duplicate records. To make things worse, valuable
Address Standardization Guide – What, Why, and How to Create a Standard Address Format?
Last Updated on February 16, 2026 Inaccurate and incomplete address data can cause your mail deliveries to be returned. In fact, the US postal
Mastering Data Management for Data Matching: Key Features and Requirements for Building an Effective Data Catalog
Last Updated on July 11, 2024 Data matching helps ensure that disparate data sources are accurately aligned, cleansed, and ready for use. And that’s
Advanced Data Clean and Match Techniques: A Comparative Review of Data Ladder vs. WinPure
Last Updated on July 11, 2024 Data cleaning and matching are critical processes for maintaining data integrity and deriving actionable insights from large datasets.
What Is Data Integrity and How Can You Maintain It?
Last Updated on January 5, 2026 67% of data and analytics professionals do not fully trust the data their organizations rely on for decision-making.
How to Improve Data Quality: Define, Design, and Deliver
Last Updated on January 15, 2025 76% of organizations say data-driven decision-making is their top goal for 2025. However, 67% of data and analytics
Guide to pattern matching: What it means and how to do it?
Last Updated on February 16, 2026 Finding patterns is easy in any kind of data-rich environment; that’s what mediocre gamblers do. The key is
Data Standardization Guide: Types, Benefits, and Process
Last Updated on February 16, 2026 Poor data standardization is a hidden profit killer. When customer names, products, or sales figures appear in different
Data Integration Explained: Definition, Types, Process, and Tools
Last Updated on September 24, 2024 With 89% of employees reporting sifting through up to six data sources daily to find relevant information, data
How poor data quality impacts a recession survival plan
Last Updated on April 8, 2024 “You get recessions, you have stock market declines. If you don’t understand that’s going to happen, then you’re
8 Principles of Data Management
Last Updated on February 16, 2026 An average enterprise – with 200-500 employees – uses about 123 SaaS applications to digitize their business processes.
Data Quality Management: What, Why, How, and Best Practices
Last Updated on January 12, 2026 “Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction, and