The debate on machine learning vs. deep learning has gained considerable steam in the past few years. The fundamental strength of both these technologies lies in their ability to learn from available data. Though both of these offshoot AI technologies triumph in “learning algorithms,” the manner in which machine learning (ML) algorithms learn is very […]
The Future of Analytics: What is All the Hype About?
Expert’s ears immediately perk up upon attending a talk about how to get big insights from analytics. After all, analytics has become the new hot topic of the day. However, asked Nipa Basu, during her keynote presentation The Future of Analytics at the DATAVERSITY Enterprise Analytics Online Conference: “What is the difference between hype and […]
Data Science and AI Use Cases
A business use case is generally defined as a sequence of business actions that lead to a predetermined, value-added outcome. Data Flair shares the Top 6 Data Science Use Cases slated to bring in another industrial revolution. From banking to transportation in the physical business world, and from social media to e-commerce on the digital business […]
Kubernetes Fundamentals: Facilitating Cloud Deployment and Container Simplicity
Kubernetes (sometimes abbreviated to “kube”) is open-sourced, was originally developed by Google, and organizes containers into logical units for transport and use in the cloud. Containers support the construction of self-contained environments capable of transporting data, and the software supporting it. Containers are, ultimately, a way to package software and other application components. It is […]
Artificial Intelligence, Machine Learning, and Deep Learning Explained
The first reference to artificial intelligence was in a paper written by Alan Turing in 1950, entitled Computing Machinery and Intelligence, where he asked the question, “Can machines think?” Turing’s article, as well as a 1977 paper entitled History of Artificial Intelligence by P. McCorduck are recommended reading for those wanting a greater understanding of […]
So You Want to be a Cloud Engineer?
It has been predicted that “cloud engineer” will be among the top ten in-demand IT jobs in 2021. There is currently a great need for cloud engineers, primarily because a significant number of organizations are moving their business processes to the cloud. As more organizations shift to cloud data storage, the demand for cloud engineers […]
Data Architecture: One Size Does Not Fit All
There has never been a time when more options were available to stand up a process-driven and/or platform-driven Data Architecture. In recent years, some companies find themselves with an embarrassment of riches, having every tool known to humankind. Using tools à la carte, with a different tool for each solution, works for some organizations. Other […]
A Brief History of the Hadoop Ecosystem
In 2002, internet researchers just wanted a better search engine, and preferably one that was open-sourced. That was when Doug Cutting and Mike Cafarella decided to give them what they wanted, and they called their project “Nutch.” Hadoop was originally designed as part of the Nutch infrastructure, and was presented in the year 2005. The […]
Deep Learning Demystified
The “deep” in deep learning refers to the number of hidden layers involved in the design. Deep learning is a way of training artificial intelligence (AI) to recognize specific data, such as speech or faces, and to make predictions based on previous experiences. Unlike machine learning, which organizes and sends data through predefined algorithms, deep […]
Working with Metadata Management Frameworks
Metadata Management will grow into 2021 and beyond. According to a DATAVERSITY® Trends in Data Management Report, 84 percent of business respondents had a Metadata Management initiative in place or had plans for one. MarketWatch, a consulting firm, expects massive growth by 2026. How much success a company will have with Metadata Management will depend […]