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 […]
How to Democratize Data Science
Efforts to democratize Data Science can be described as creating an environment that allows people with little expertise to perform Data Science research. This approach can be especially useful for businesses desperate to access the skills of a data scientist, but unable to hire one. A variety of user-friendly analytics tools have become available to support staff […]
Data Science Metrics: Purpose and Uses
When one thinks of “metrics” in the context of Data Science, the term might denote raw numbers as in descriptive metrics, qualitative labels as in marketing analytics, or comparative labels as in website analytics. Metrics come in many different forms and structures, but the primary objective of Data Science metrics is to measure and report […]
Analytics Solutions: Applications and Use Cases
Data and analytics are particularly critical to today’s businesses because they improve strategic decision-making. Analytics solutions and use cases provide customers with added value in health care, retail, higher education, manufacturing, and other industries that capture a lot of valuable data. By harnessing different types of analytics available, organizations across varying industries can understand how products are […]
How to Build a High-Performance Analytics Team
When most people think of analytics, they tend to picture a rigidly left-brained data scientist more at home with computer programming than creativity. But analytics leader and author John K. Thompson challenges such a notion. During his keynote presentation at DATAVERSITY’s Enterprise Analytics Online event, he proposed instead that the members of an analytics team can be […]
Data Science Solutions: Applications and Use Cases
Data Science is a broad field with many potential applications. It’s not just about analyzing data and modeling algorithms, but it also reinvents the way businesses operate and how different departments interact. Data scientists solve complex problems every day, leveraging a variety of Data Science solutions to tackle issues like processing unstructured data, finding patterns […]