Resources
Blogs
Your Complete Guide to Obtaining a 360 Customer View
If you’ve landed here, chances are you already know you want a 360-customer view for all the customer data in your organization. Cutting right to
The Complete Guide to Data Cleaning Tools, Solutions & Best Practices for Enterprise Level
Being data-driven is an ambition for most companies today, however, data quality is an underlying challenge that hinders companies from following through with this ambition.
What is a Postal Code and Why is it Important for Address Verification and Validation?
You may have often heard of ZIP+4 address verification when implementing a data cleansing and matching activity. But do you know exactly what is a
Key Components that Should be Part of Your Operational Efficiency Goals
Operational efficiency remains a key challenge for enterprise-level businesses, especially in an age when customers have very little patience and the competition is high. It
How Transaction Matching Software Can Empower Your Financial Institution & Improve Operational Efficiency
Do your banking officers or insurance agents still manually compare spreadsheets to make sense of data? Do you still have manual journal entries as part
Data Management Trends 2020 – An Overview by Data Ladder
It won’t be possible to give an overview of data management trends 2020 without conducting an analysis of the clients and the projects we worked
Your Complete Guide to List Matching Software and Approaches
Most companies now understand that new technologies and applications must be implemented in order to upscale business operations. But implementing a data migration of a
Name Matching Software vs Algorithms: Which is Best for Your Business?
Catherine spelled as Cathy, Kath or Katharine; John entered in your system as Jon, Jonathan, or Jonny; or a Margaret who goes by Peggy when
Using Wordsmith to Remove Noise and Standardize Data in Bulk for Greater Matching Confidence
The data that flows into your organization comes in a variety of formats: inconsistent capitalization, punctuation, obscure acronyms, alpha-numeric characters living in fields they shouldn’t
What Does Data Quality Mean for Your Data Warehouse?
Bad data is why many data warehousing projects fail to deliver results; in fact, data quality in data warehouses remains a significant challenge for many
Entity Resolution for a Single Customer View
“The ability to view the customer through a single lens enables critical measurement, optimization, efficiency, and personalized use cases.” Jason Niemi, Director Digital Engagements, Kraft
Data Cleansing Tools: Improving Analytics and Business Intelligence with Clean Data
To understand and respond to trends that impact business performance, it’s critical that you know where to find corresponding data and how to tie the
Data Cleansing in the Data Warehouse: The Code-Free, Automated Approach to Maintaining Your Single Source of Truth
Data is everywhere, with total volume expected to exceed 44 trillion GBs by 2020, but rarely is it useful. Only 27% of organizations with data
Salesforce Data Cleansing 101: The Comprehensive Guide to the “Why” and “How” of Data Quality in Your CRM
Comprehensive Salesforce data cleansing guide filled with actionable solutions that can help you reduce wasted costs and increase revenue NOW!
3 Ways Data Cleansing Software Can Help Increase Your Marketing ROI
“It takes $1 to verify a record as it’s entered, $10 to cleanse and dedupe it, and $100 if nothing is done, as the ramifications
Unlock New Business Opportunities by Improving Data Quality
As villains continuously strive hard to demoralize the hero in your favorite movies and books but never succeeds, similarly, the wrong and bad data should
How Data Quality is an Important Data Lake Ingestion Challenge & What You Can Do to Ensure Your Data Lake Project is a Success
Data lakes were formed as a solution to storing unstructured data – an alternative to the restrictive nature of data warehouses. But this ease comes
Self-Service Data Preparation for Analytics Modernization
Different changes in the world of data have allowed organizations to manage their day-to-day requirements while preparing for big data future, analytics, and real-time operations.