Data and technology feel like modern and futuristic topics, but there are lessons to be learned from the past in regards to data science. This interesting information came to us from the National Institutes of Health blog post titled, “Data Science in History: Parallel Paths, 150 Years Apart.”
While the challenges of today’s data-driven world are thoroughly modern and unique, there are historical analogies that can provide helpful perspectives.
Data science is an interdisciplinary field focusing on scientific methods, processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured.
Statistics, and the use of statistical models, are deeply rooted within the field of data science. Data science started with statistics, and has evolved to include concepts/practices such as artificial intelligence, machine learning, and the Internet of Things, to name a few.
Once the doors were opened by businesses seeking to increase profits and drive better decision making, the use of data started being applied to other fields, such as medicine, engineering, and social sciences.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
