Since 2017, Perry Beaumont, PhD, has served as the head of data science and an actuary at Distinguished Programs in New York City. He also is a lecturer at Columbia University. Active in the professional community, Dr. Perry Beaumont is a regular speaker at industry conferences and the author of several books on topics such as big data.
Big data and data science are often talked about together, yet many people are unclear about the differences between the two. Big data is large amounts of structured and unstructured data coming from multiple sources. This data is generally categorized by variety, volume, and velocity. These refer to the batch of data, its format, and its size.
When analyzed, big data is capable of improving business decisions and strategic moves. However, due to the size of this data, traditional data analysis methods do not work. Further, big data cannot be stored by using traditional systems.
Meanwhile, data science, or data-driven science, is a specialized field that seeks to take knowledge or insights from different forms of data. Similar to data mining, it involves the analysis of big data.
To gain insights, data science blends algorithms, machine learning, and other analysis tools to find patterns in raw data that help solve a problem. These tools also help data scientists create new data modeling processes.
Big data and data science are often talked about together, yet many people are unclear about the differences between the two. Big data is large amounts of structured and unstructured data coming from multiple sources. This data is generally categorized by variety, volume, and velocity. These refer to the batch of data, its format, and its size.
When analyzed, big data is capable of improving business decisions and strategic moves. However, due to the size of this data, traditional data analysis methods do not work. Further, big data cannot be stored by using traditional systems.
Meanwhile, data science, or data-driven science, is a specialized field that seeks to take knowledge or insights from different forms of data. Similar to data mining, it involves the analysis of big data.
To gain insights, data science blends algorithms, machine learning, and other analysis tools to find patterns in raw data that help solve a problem. These tools also help data scientists create new data modeling processes.
