Resources
Blogs
Guide to data survivorship: How to build the golden record?
92% of organizations claim that their data sources are full of duplicate records. To make things worse, valuable information is present in every duplicate that
Standard Address Format: Address Standardization Guide – What, Why, and How?
Inaccurate and incomplete address data can cause your mail deliveries to be returned. In fact, the US postal service handled 6.5 billion pieces of UAA
Mastering Data Management for Data Matching: Key Features and Requirements for Building an Effective Data Catalog
Data matching helps ensure that disparate data sources are accurately aligned, cleansed, and ready for use. And that’s where an effective data catalog becomes essential
Advanced Data Clean and Match Techniques: A Comparative Review of Data Ladder vs. WinPure
Data cleaning and matching are critical processes for maintaining data integrity and deriving actionable insights from large datasets. This review dives into the advanced techniques
What is data integrity and how can you maintain it?
While surveying 2,190 global senior executives, only 35% claimed that they trust their organization’s data and analytics. As data usage surges across various business functions,
How to Improve Data Quality: Define, Design, and Deliver
76% of organizations say data-driven decision-making is their top goal for 2025. However, 67% of data and analytics professionals don’t fully trust the data used
Guide to pattern matching: What it means and how to do it?
Finding patterns is easy in any kind of data-rich environment; that’s what mediocre gamblers do. The key is in determining whether the patterns represent signal
Data Standardization Guide: Types, Benefits, and Process
Poor data standardization is a hidden profit killer. When customer names, products, or sales figures appear in different formats across systems (and often even within
Data Integration Explained: Definition, Types, Process, and Tools
With 89% of employees reporting sifting through up to six data sources daily to find relevant information, data sprawl emerges as a major culprit undermining
How poor data quality impacts a recession survival plan
“You get recessions, you have stock market declines. If you don’t understand that’s going to happen, then you’re not ready. You won’t do well in
8 Principles of Data Management
An average enterprise – with 200-500 employees – uses about 123 SaaS applications to digitize their business processes. With large amounts of data being generated
Data Quality Management: What, Why, How, and Best Practices
“Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction, and skillful execution; It represents the wise choice
How to Improve Data Quality in Financial Services
24 percent of insurers say that they are ‘not very confident’ about the data they use to assess and price risk. Corinium Intelligence The economic
Data quality in healthcare – Benefits, challenges, and steps for improvement
38 percent of U.S. healthcare providers have incurred an adverse event within the last two years due to a patient matching issue. Survey from eHI
Common data quality issues in the retail industry and how to fix them
In the previous blog The role of data quality in the world of retail, we discussed the role clean data plays in the retail industry
The Role of Data Quality in Retail Industry
We’ve all experienced the thrill of a perfectly timed Netflix recommendation or the joy of discovering a new favorite song in your Spotify playlist. It
12 Most Common Data Quality Issues and Where Do They Come From
In early 2022, Unity Technologies faced an unexpected data quality issue—one that cost the company $110 million. Resulting from the ingestion of flawed data by
Building a case for data quality: What is it and why is it important
According to an IDC study, 30-50% of organizations encounter a gap between their data expectations and reality. A deeper look at this statistic shows that: