The two terms data analysis and data visualization seem to have become synonymous in everyday language in the wider data community. Numerous job adverts focus on data visualization skills while not ...

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...

Editor’s note: This is the third article in a four-part series that is part of a larger initiative the AICPA Auditing Standards Board (ASB) has undertaken to understand and support technology use in ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Businesses have relied on experiences and intuition-based decisions from senior leaders for growth for decades. These methods, while still being highly valuable, have been augmented by data-driven ...

In 2012, Hurricane Sandy rocked the East Coast in a way the region was largely unprepared for. While the Gulf states have had plans in place for withstanding hurricanes, the northeast dedicated ...

For decades, visualization was the final stop on the data journey. It was optional—"good to have" on top of data analytics. Analysts would gather numbers, then clean and process, and only at the end ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

Data modeling is the procedure of crafting a visual representation of an entire information system or portions of it in order to convey connections between data points and structures. The objective is ...

The table below shows my favorite go-to R packages for data import, wrangling, visualization and analysis — plus a few miscellaneous tasks tossed in. The package names in the table are clickable if ...