DQM is becoming a core capability for organizations that need to make better decisions with data. What are the responsibilities of different roles in DQM? Image: WrightStudio/Adobe Stock Data quality ...

While companies may share common ground when it comes to their data quality problems, data quality tools and strategies are not one-size-fits-all solutions to the problem. Each company should approach ...

Everyone understands data is important, but many business leaders don’t realize how impactful data quality can be on day-to-day operations. In my experience, nearly all process breakdowns have root ...

Data quality management is a crucial part of any data integration process. It may be considered the first step to the integration process, as quality data is the key to achieving profitable insights.

On a recent executive outreach call, a leader from a large enterprise shared how their 120,000 users were actively involved in improving data quality across the organization. Intrigued, I reviewed ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

1. The Data Quality Assessment Framework (DQAF) was developed to address the Executive Board's interest in data quality as expressed during the December 1997 discussion of the Progress Report on the ...

Design thinking is critical for developing data-driven business tools that surpass end-user expectations. Here's how to apply the five stages of design thinking in your data science projects. What is ...

Utilities are becoming increasingly skilled at adapting to changes brought on by the digital age: pressure from automation, disruption from new technology, and challenges with how to ingest, manage, ...

If your business is struggling to manage customer profiles and customer master data across different departments, Customer Master Data Management (CMDM) solutions could be the answer. These tools ...