Resources
Blogs
Advanced Data Clean and Match Techniques: A Comparative Review of Data Ladder vs. WinPure
Last Updated on July 11, 2024 Data cleaning and matching are critical processes for maintaining data integrity and deriving actionable insights from large datasets.
What Is Data Integrity and How Can You Maintain It?
Last Updated on March 3, 2025 67% of data and analytics professionals do not fully trust the data their organizations rely on for decision-making.
How to Improve Data Quality: Define, Design, and Deliver
Last Updated on January 15, 2025 76% of organizations say data-driven decision-making is their top goal for 2025. However, 67% of data and analytics
Guide to pattern matching: What it means and how to do it?
Last Updated on September 11, 2024 Finding patterns is easy in any kind of data-rich environment; that’s what mediocre gamblers do. The key is
Data Standardization Guide: Types, Benefits, and Process
Last Updated on November 14, 2025 Poor data standardization is a hidden profit killer. When customer names, products, or sales figures appear in different
Data Integration Explained: Definition, Types, Process, and Tools
Last Updated on September 24, 2024 With 89% of employees reporting sifting through up to six data sources daily to find relevant information, data
How poor data quality impacts a recession survival plan
Last Updated on April 8, 2024 “You get recessions, you have stock market declines. If you don’t understand that’s going to happen, then you’re
8 Principles of Data Management
Last Updated on April 8, 2024 An average enterprise – with 200-500 employees – uses about 123 SaaS applications to digitize their business processes.
Data Quality Management: What, Why, How, and Best Practices
Last Updated on September 26, 2024 “Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction, and
How to Improve Data Quality in Financial Services
Last Updated on October 17, 2024 24 percent of insurers say that they are ‘not very confident’ about the data they use to assess
Data quality in healthcare – Benefits, challenges, and steps for improvement
Last Updated on August 13, 2024 38 percent of U.S. healthcare providers have incurred an adverse event within the last two years due to
Common data quality issues in the retail industry and how to fix them
Last Updated on April 8, 2024 In the previous blog The role of data quality in the world of retail, we discussed the role
The Role of Data Quality in Retail Industry
Last Updated on November 14, 2024 We’ve all experienced the thrill of a perfectly timed Netflix recommendation or the joy of discovering a new
12 Most Common Data Quality Issues and Where Do They Come From
Last Updated on October 16, 2024 In early 2022, Unity Technologies faced an unexpected data quality issue—one that cost the company $110 million. Resulting
Building a case for data quality: What is it and why is it important
Last Updated on April 8, 2024 According to an IDC study, 30-50% of organizations encounter a gap between their data expectations and reality. A
Data quality API: Functions, architecture, and benefits
Last Updated on April 8, 2024 While surveying 1900 data teams, more than 60% cited too many data sources and inconsistent data as the
Batch Processing versus Real-Time Data Quality Validation
Last Updated on November 11, 2024 Research shows that while 24% of data teams use tools to find data quality issues, most of their
The Impact of Poor Data Quality: Risks, Challenges, and Solutions
Last Updated on September 12, 2024 Poor data quality can have devastating risks on your business. Most organizational workers realize the impact of of
Designing a Data Quality Management Framework
Last Updated on October 3, 2024 Data is the lifeblood of decision-making in the business world today. Yet as revealed by the State of
5 data quality processes to know before designing a DQM framework
Last Updated on August 25, 2023 Most companies trying to become data-driven cite poor data quality as one of the top 5 challenges. Invesp