There are many factors that have started making businesses restless and eager to dive into the newest intelligent technologies for their Data Management practices. The business operators have sighed with relief knowing that they no longer have to engage dedicated talents for advanced model development or cloud infrastructure planning. The idea of “managed (hosted) Data […]
Graph Databases: Updates on Their Growing Popularity
Graph databases became recognized as a database design in 2006, when Tim Bernes-Lee developed the concept of a huge database called the “linked data.” This concept became the basis of graph storage, and could display how organizations, people, and items or entities are associated, or “interconnected” with one another, and the nature of the relationships. […]
Advances in Machine Learning
There is little doubt machine learning has become one of the most powerful technologies in the last decade. The emphasis on “learning” in machine learning allows computers to make better and better decisions, based on previous experiences. Advances in this technology have allowed for recent breakthroughs that promote faster and more efficient business intelligence, using […]
Data Management and the Internet of Things
Billions of things with sensors surround people and their lives. These Internet of Things (IoT) interact with people, homes, factories, workplaces, cities, farms, and vehicles. Gartner predicts that by 2021, IoT technology will be in 95 percent of electronics for new product designs, from wearables to medical devices and beyond. IoT promises useful information, allowing […]
2020 DATAVERSITY Top 20
With 2020 now behind us, we here at DATAVERSITY are taking a moment to look back on the hits and misses of this unprecedented year. What content did you, our readers, seek out most during challenging times? Which topics helped you succeed as a data professional, and what should we focus more on in 2021 […]
So You Want to Be a Citizen Data Scientist?
The job responsibilities of a citizen data scientist include dealing with new data, using automated tools to process big data, and creating additional models to gain additional insights. Their primary job is not to make predictions directly from big data, nor develop prescriptive analytics, but to build models and use tools that accomplish those goals. […]
The Importance of Graph Databases in Business Analytics
Augmented analytics is one of the top 10 technologies Gartner identified with the potential to cause significant digital disruption in the next three to five years. The hallmark of augmented analytics is its high reliance on AI and ML technologies. AI and ML together will transform enterprise Data Management in the coming years, and many […]
Building Machine Learning Program Success
Kristen Serafin, associate director at Financial Industry Regulatory Authority (FINRA) and Lizzie Westin, lead systems analyst at FINRA, speaking at DATAVERSITY® Enterprise Analytics Online Conference, shared how they were able to gain traction for a successful machine learning program. The presentation was titled Ushering in the Age of Machine Learning. FINRA is a private, not-for-profit […]
Streaming Analytics: The Value is in the Action
“When we’re talking about streaming analytics, we’re talking about flipping our traditional paradigm a little bit and thinking about how we bring analytics to our data, and not necessarily data to our analytics,” said Kimberly Nevala, the Director of Business Strategies for SAS Best Practices, while discussing streaming analytics during the DATAVERSITY® Enterprise Analytics Online […]
Automation and AI: Challenges and Opportunities
Businesses across the globe are fascinated with the idea of AI and automation because this advanced technology promises operational efficiency, enhanced processes, and substantial cost savings. However, AI and its allied technologies have also created uncertainties, confusion, and doubts about the human capability for adopting, deploying, and executing these magical systems in actual business situations […]