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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
It is challenging to correlate a data problem to business risk or impact. Poor data quality can have devastating risks on your business. Most organizational
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
According to Seagate’s Rethink Data Report 2020, 44% of enterprise data is lost, and only 56% is made available for use. Moreover, out of the
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