Data Deduplication for Government Agencies: Risks and Solutions
For most companies, duplicate entries can signal warning signs of potential missed revenue targets, negative brand perception, and poor campaign response. For government agencies, however,
Why an Address Matching Software is Better Suited for Improving Mailing Accuracy
Matching addresses to assign location coordinates is vital for lead or customer outreach campaigns or shipping orders for businesses. While scripting methods can be used
Using Data Scrubbing Software for Enterprise-wide Data Consistency: A Detailed Guide
Ever found yourself in the middle of a campaign or regulatory compliance report only to find your efforts wasted by the sheer number of typos, omissions, system-led errors and varied formats due to
Record Linkage in Education Sector: Challenges, Limitations, and Tips to Improve Data Accuracy
Record linkage is often a necessary component to effectively execute different educational initiatives. Whether it is measuring the performance of students and teachers overtime and
Data Quality Testing – A Quick Checklist to Measure and Improve Data Quality
Don’t wait for a data migration event to test your data quality. Perform data quality tests now before it gets too late. Here’s everything you need to know!
4 Ways List Matching Software Tools Can Jumpstart Your Marketing Campaigns
Name and address data are critical for determining the accuracy of a company’s market and customers, and in turn, their product positioning. Banks, healthcare providers
Achieving High Precision Data Scrubbing with Advanced Name and Address Transformations
Name and address data is critical to determining the accuracy of a company’s market and customers, and subsequently, their product positioning. Banks, healthcare providers and
Name Matching Challenges: How Much Do Financial Institutions Lose Due to Unresolved Customer Identities?
Bad data is arguably the most significant challenge faced by banks and large financial enterprises. According to Baker Tilly director Ollie East, US businesses lose around
A Detailed Guide to Using Entity Resolution Tools for Enterprise Data Projects
Dirty, unstructured structured data, dozen-plus name variations, and inconsistent field definitions across disparate sources. This can of worms is an almost staple occupational hazard for
Why Fuzzy Address Matching Is Critical for Cleaner Lists
If the thought of address matching across half a dozen sources has crossed your mind before, you know it is anything but a walk in
The Importance of Data Profiling for Data Management
Any data professional will agree that having accurate, clean, and consistent data is critical for meeting business objectives. And yet, you will hear about only
A Quick Guide to Record Linkage Software
To understand the complete customer story and extract benefit, it is necessary to integrate and merge data such that each record represents a single entity.
The Importance of Data Cleansing and Matching for Data Compliance
Data compliance standards (such as GDPR, HIPAA, and CCPA, etc.) are compelling corporations to revisit and revise their data management strategies. Although each standard enforces
Using a self-service tool for data preparation
Data cleansing and data preparation are not the same. When you are cleaning data, you are removing inaccuracies, invalidities, and junk from it. But when
Using Data Matching to Resolve Identity Resolution Challenges
Consumers interact with a brand through hundreds of touchpoints across devices, platforms, and channels. During the buyer’s journey, consumers use 3-4 internet-connected devices. And by
How to Improve the Quality of Householding Data and Better Understand Your Customers
A household consists of multiple separate accounts that belong to individuals who are related and are physically living together.
The Duplicate Data Dread – A Guide to Data Deduplication
Duplicate data is a serious problem that affects an organization’s insights, eats up expensive storage space, messes up customer information & leads the business into
Comment identifier les données manquantes, assurer l’exhaustivité des données et maintenir l’exactitude de vos données ?
Les données du monde réel auront toujours des valeurs incomplètes ou manquantes, surtout si elles sont recueillies auprès de plusieurs sources. Des données incomplètes peuvent