Click to learn more about author John Ottman. The goal of digital transformation remains the same as ever – to become more data-driven. We have learned how to gain a competitive advantage by capturing business events in data. Events are data snap-shots of complex activity sourced from the web, customer systems, ERP transactions, social media, […]
Why Graph Databases Are an Essential Choice for Master Data Management
Click to learn more about author Brian Platz. Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. It’s outdated, it’s clunky, and it was built for a different era. […]
Three Critical Success Factors for Master Data Management
Click to learn more about author Bill O’Kane. As the Master Data Management (MDM) solutions market continues to mature, it’s become increasingly clear that the program management aspects of the discipline are at least as important, if not more so, than the technology solution being implemented. After spending eight years as a Gartner analyst covering […]
Dear Laura: Our Data Governance Leader Quit
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 […]
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 […]
Moving Unstructured Data Is Risky and Pricey, but Critical: Five Steps to Improve It
Click to learn more about author Daniel Esposito. It’s time-consuming – and often very costly – for enterprises to perform a network-attached storage (NAS) or object data migration. As moving unstructured data has proliferated over the past decade, with as much as 90% of all data defined as unstructured data, the task has become increasingly […]
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 […]
Messy Data Shouldn’t Stop Machine Learning in Its Tracks
Click to learn more about author Jon Reilly. Businesses are creating data at an incredible pace that will only accelerate. In fact, data storage company Seagate predicts it will pass a yearly rate of “163 zettabytes (ZB) by 2025. That’s ten times the amount of data produced in 2017.” Moore’s Law – the principle that […]
Three Reasons to Take a More Holistic Approach to Data Management
Click to learn more about author Olivia Hinkle. Taking a holistic approach to data requires considering the entire data lifecycle – from gathering, integrating, and organizing data to analyzing and maintaining it. Companies must create a standard for their data that fits their business needs and processes. To determine what those are, start by asking […]
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 […]