Hyperautomation describes a mixture of advanced technologies – robotics, artificial intelligence, machine learning – currently being used to make automated processes drastically more efficient and to augment humans. It encompasses a range of tools which can be automated, especially the more sophisticated aspects of automation, including analysis, discovery, design, measuring, monitoring, and reassessing. To function […]
Data Science vs. Machine Learning vs. AI
In the data economy, data is king. Today, any business – small, medium, or large – thrives on its data assets. The recent trend of offering data-driven insights as a service has opened up a profitable revenue channel for businesses. Cloud computing and hosted analytics have brought data-as-a-service to the desktops of ordinary business users, […]
Are Data Scientists Needed in the Self-Service Analytics World?
As the world becomes increasingly data-driven, businesses are turning to self-service analytics to enable business users to perform their own data analysis tasks. In self-service analytics, business users can access and analyze data without assistance or support from IT personnel or data scientists. Direct access to ML-powered analytics platforms allows them to make better business […]
How to Build a Career in Data Science
Considering a career in Data Science? Good news: The U.S. Bureau of Labor Statistics estimates that the employment rate for data scientists will grow by 36% between 2021 and 2031, with 40,500 more jobs expected to be created in that time. As the amount of data generated globally increases at a rapid pace, so too does the […]
Data Science 101
Data Science is an interdisciplinary field that allows businesses to study and analyze large volumes of data and derive meaningful information from it. It combines elements of artificial intelligence, machine learning (ML), and knowledge engineering to uncover insights from data. Data Science uses ML techniques such as supervised learning, unsupervised learning, deep learning, and reinforcement learning […]
A Brief History of Semantics
As a word, “semantics” was first used by Michel Bréal, a French philologist (a language historian),in 1883. He studied how languages are organized, how languages change as time passes, and the connections within languages. Gen erally speaking, semantics is the study of language and its meaning. More specifically, semantics can be used to describe how […]
Data Science Trends in 2023
Data and analytics are helping change the business world and as we head into 2023, this is the right time to predict how to work with data, by getting ready with the new year’s top data and analytics trends. Some of the top data-related trends driving the market today include advances in Data Science, data […]
Developing a Successful Data Science Project
While Data Science practitioners, aspirants, and enthusiasts often get caught up in the business benefits of Data Science, it is equally important to keep a close watch on the common pitfalls that need to be avoided to launch a successful Data Science project. By identifying and exploring why some initiatives fail, data scientists can learn […]
2022 DATAVERSITY Top 20
Every December, we here at DATAVERSITY set aside time to dig through our data and reflect on the hits and misses of the year. We want to know: Which content did you, our data-loving readers, consume and enjoy the most? Which Data Management topics and experts helped you learn valuable new skills, succeed at your […]
What Makes a Great Data Scientist in 2023?
A great data scientist combines expert knowledge of various interrelated academic disciplines to help global enterprises make agile decisions for improved business performance. Data scientists use statistics, mathematics, data mining, and computer science to analyze data sets for observable trends and patterns. They are also experts in data collection and storage methods. The Bureau of Labor Statistics had predicted […]