Resources
Blogs
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:
Data quality API: Functions, architecture, and benefits
While surveying 1900 data teams, more than 60% cited too many data sources and inconsistent data as the biggest data quality challenge they encounter. But
Batch Processing versus Real-Time Data Quality Validation
Research shows that while 24% of data teams use tools to find data quality issues, most of their problems still go unresolved. This means that
The Impact of Poor Data Quality: Risks, Challenges, and Solutions
Poor data quality can have devastating risks on your business. Most organizational workers realize the impact of of poor data quality, but it is hard
Designing a Data Quality Management Framework
Data is the lifeblood of decision-making in the business world today. Yet as revealed by the State of Data Quality Report 2022, less than half
5 data quality processes to know before designing a DQM framework
Most companies trying to become data-driven cite poor data quality as one of the top 5 challenges. Invesp published a report where they discovered that
The definitive buyer’s guide to data quality tools
A recent survey reported that the top KPI for data teams in 2021 was data quality and reliability. But the majority of the respondents said
Building a Data Quality Team: Roles and Responsibilities to Consider
Despite organizations claiming their data strategies are effective, only 56% report achieving their data goals in 2023, and a staggering 66% of enterprise data remains
What is the Difference between Data Quality and Master Data Management?
We have delivered data quality solutions to Fortune 500 companies for over a decade. We often come across clients who are confused about how to
