Data Cleansing: Why It’s Important

Click to learn more about author Avee Mittal. Data cleansing is an important step to prepare data for analysis. It is a process of preparing data to meet the quality criteria such as validity, uniformity, accuracy, consistency, and completeness. Data cleansing removes unwanted, duplicate, and incorrect data from datasets, thus helping the analyst to develop […]

The Three Pillars of Trusted AI

Click to learn more about author Jett Oristaglio. As AI becomes ubiquitous across dozens of industries, the initial hype of new technology is beginning to be replaced by the challenge of building trustworthy AI systems. We’ve all heard the headlines: Amazon’s AI hiring scandal, IBM Watson’s $62 million failure in oncology, the now-infamous COMPAS recidivism […]

Dear Laura: Data Democratization

Click to learn more about author Laura Madsen. Welcome to the Dear Laura blog series! As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. I’ll be sharing these questions and answers via this DATAVERSITY® series. Last year I wrote […]

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