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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 the world of retail
According to an Accenture survey, over 75% of consumers are more likely to purchase from retailers who know their name and buying preferences, and about
12 most common data quality issues and where do they come from
According to O’Reilly’s report on The state of data quality 2020, 56% of organizations face at least four different types of data quality issues, while
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
A recent survey shows that 24% of data teams use tools to find data quality issues, but they are typically left 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 Framework for Data Quality Management
According to O’Reilly’s report on The state of data quality 2020, 56% of organizations face at least four different types of data quality issues, while
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
A guide to master data management: What, why, who, and how
The need for master data management A recent Deloitte Digital report shows that an average business uses 16 applications to leverage customer data and about
Data quality dimensions – 10 metrics you should be measuring
“As organizations accelerate their digital business efforts, poor data quality is a major contributor to a crisis in information trust and business value, negatively impacting
Data quality measurement: When should you worry?
In March 2017, Rescue 116 crashed into a 282ft obstacle – the Blackrock Island off the County Mayo coast. Further investigations revealed that the CHC