For healthcare data strategy projects, there are four essential elements to turn aspiration into a plan for recurring ...

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 ...

AI’s true promise is turning clinical development from a bottleneck into a throughput engine for human health. Drug discovery ...

Data is the foundation of innovation, agility and competitive advantage in today’s digital economy. As technology and business leaders, your strategic initiatives, from AI-powered decision-making to ...

It can be tough to manage data manually, and doing so can sometimes lead to errors or inefficiencies. Spreadsheets can get overly complex, and data quality can suffer. This has become a large enough ...

Data architects live in a world caged by bars of process, standards, and documented procedures—things many would consider a high ceremony lifestyle. As an industry, information technology has been ...

Data quality initiatives are not wide­spread enough to enable consistent qual­ity, and the discovery of issues is often through informal processes. The greatest risk factors to data quality come from ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Data has grades. Much like olive oil, flour, gasoline, beef ...

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 ...

Enhance your data strategy with effective data quality and data governance practices. Learn their differences and how to integrate the strategies successfully. Image: Dmitry/Adobe Stock Data quality ...