Resources
Blogs
Data Matching Applications: Complete Guide for 2026Â
Last Updated on March 11, 2026 Most organizations are working with the same customer in three different databases and don’t know it. Data matching
THE IMPACT OF DATA MATCHING ON THE WORLD OF FINANCE
Last Updated on February 4, 2026 In today’s fast-paced technological environment, the success of every business relies on a data-driven model. However, achieving this
Importance of Data Cleansing in the Process of Record Linkage & Entity Resolution
Last Updated on February 4, 2026 What is Record Linkage? The process of collecting all data associated with a single person that is scattered
The impact of poor data matching on Marketing Campaigns
Last Updated on February 24, 2026 Data matching plays an important role in helping marketing managers to devise marketing campaigns. With the advent of
The Role of Data Matching in Fraud Prevention
Last Updated on February 27, 2026 Quick Summary Organizations lose 5% of revenue to fraud annually—$5.38 trillion globally [ACFE, 2024]. Companies using data matching
Customer Retention vs. Customer Attrition: How Clean Data Tips the Balance
Last Updated on March 5, 2026 Here are the customer retention and attrition statistics that should be shaping your strategy right now: Customer churn
Pattern Builder in DataMatch Enterprise: Data Parsing & Standardization for Better MatchingÂ
Last Updated on March 6, 2026 In enterprise data environments, matching accuracy doesn’t begin with algorithms. It begins with clean, well-structured input data. Before fuzzy matching,
ZIP plus 4 plus 2 equals ZIP plus 6
Last Updated on April 10, 2026 Most people know their five-digit ZIP Code. A fair number know about ZIP+4. ZIP+6 catches almost everyone off
How Poor Data Quality Increases Data Breach Risk And How to Fix It
Last Updated on March 17, 2026 Most conversations about data breaches focus on what happens after an attacker gets in: stolen credentials, ransomware, patching
What AI-Ready Data Actually Looks Like (and Why Most Enterprise Databases Aren’t There Yet)
Last Updated on March 25, 2026 Most organizations assume their data is good enough for AI. It usually isn’t. A 2024 study by Precisely
Marketing Analytics Made Easier
Last Updated on April 25, 2022 As a marketing analyst, you’re expected to know the ins, outs and metrics of your company’s marketing efforts.
Cleaning Big Data the Easy Way
Last Updated on October 24, 2022 Cleaning big data usually invokes big stress levels. With the advancements we’ve seen in technology over the years,
Data Preparation for Analytics
Last Updated on September 13, 2022 As users seek to go beyond canned reports and spreadsheets to employ sophisticated visual analytics to drive decisions
The Importance of a Data Quality API
Last Updated on September 5, 2022 When it comes to data quality management, few things cause as much grief as having to download data
Think Address Verification is an Option?
Last Updated on April 25, 2022 Address verification is vital for any business. Inaccurate addresses can be a costly problem for your organization and
Bad data equals bad customer experience
Last Updated on April 25, 2022 In a competitive world with seemingly endless choices and price-wars, there’s one thing that can truly set you
The Cost of Bad Data Quality
Last Updated on August 11, 2022 How much is bad data quality costing you? Like many modern businesses, you probably rely heavily on your
Data Preparation: Managing Data in the Real World
Last Updated on October 24, 2022 By Jack Bradford, Senior Product Specialist Data preparation and matching is a growing profession that requires an in-depth
How an Address Verification Software Can Resolve Your Address Woes
Last Updated on April 9, 2026 Let’s face it. Your company’s address data is messy. In fact, you probably don’t even have an address
How to Use Data Profiling to Get an Overview of Your Organization’s Data Quality & Identify Areas of Improvement
Last Updated on January 11, 2026 Whether you’re aiming for migration to a new CRM, optimizing your data for marketing or implementing data governance,