Your Complete Guide to a Successful Data Migration
If you’re reading this guide, chances are you’ve already decided to initiate a data migration project and are looking for additional guidance. Cutting right to
If you’re reading this guide, chances are you’ve already decided to initiate a data migration project and are looking for additional guidance. Cutting right to
In this blog, we will take an in-depth look at fuzzy matching, the go-to approach for data deduplication and record linkage. We will cover: What
In this blog, we will discuss what is data matching and the following benefits of it that help businesses enhance business intelligence and directly impact
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,
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
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 is often a necessary component to effectively execute different educational initiatives. Whether it is measuring the performance of students and teachers overtime and
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!
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
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
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
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