Resources
Whitepapers
How to ensure a successful CRM migration
You’ve tested out the migration process with sample data and it went well, so now you decide to go through with the actual migration. And
How legacy systems and bad data quality hinders a digital transformation plan
Introduction Cloud. Automation. Analytics. With the rapid influx of tech developments and trends that affect business, organizations are doing everything they can to embrace digital
How best-in class fuzzy matching solutions work: Combining established and proprietary algorithms
Data is no longer just records of customer names, contact numbers, or addresses. It’s a combination of information obtained from multiple sources and it’s mostly
Establishing data quality standards for business success
Does your data look like this? Do you have data stored in Salesforce, Fusion, Excel, and other asset management systems? Do you have entries with
Data quality tools and their application in the education industry
Poor Record Linkage & Poor Results Anyone working in education understands that student achievement is not linear. Many factors come into play from strong study
10 things to check when profiling your data
Data profiling is a crucial part of data conversion, migration, and data quality projects. In fact, it is the first step in understanding the scope
Creating the golden record with Data Ladder’s merge purge feature
As much as companies enjoy basking in big data, they cannot still manage, store, and handle data. For the most part, data is stored in
Anti-money laundering screening and data matching
1.0 Executive Summary – The AML Compliance Dilemma AML compliance programs demand accurate and timely information. Yet, 87% of organizations’ financial crime risk management processes
A quick step by step guide to preparing data for cloud migration
Traditionally, data migration involved extracting, transforming, and loading data from relational databases to the central enterprise data warehouse where it could be put to use
