Data analysis is performed in many different fields and on many different types of data. Most fields call it something different. The following list comes straight from Jeff Leek’s Data Analysis Coursera class.
Name of Data Analysis by Data Type
- Biostatistics for medical data
- Data Science for data from web analytics
- Machine learning for data in computer science/computer vision
- Natural language processing for data from texts
- Signal processing for data from electrical signals
- Business analytics for data on customers
- Econometrics for economic data
The type of analysis is very similar for all fields, but what separates data science and machine learning from the others is the 3 V’s of big data. Data science and machine learning deal with a greater Volume of data, Variety of data, and Velocity (speed at which new data appears) of data. Because it is becoming cheaper and easier to store massive amounts of data than ever before, I think the other fields are beginning to realize the potential in big data. Signal processing is definitely becoming an area with big data, due to the fact that electrical sensors are everywhere.
What are your thoughts? Do you see any real differences in the data analysis performed for the data types above?