The two commonly used terms in Data Science, particularly in the field of Business Intelligence are Data Analysis and Data Analytics. Apart from these, the other common terms are Business Analytics, Data Warehouse, Data Mart, and Data Lake. Surprisingly, each and every term might sound alike but are actually different.
Data vs. Datum
Data is a set of values of qualitative or quantitative variables about one or more persons or objects, whereas, Datum is a single value of a single variable. In today's era, we deal with enormous amounts of data from various sources. As such, we need an intelligent system for the extraction process.
Analysis vs. Analytics
If we talk about Analysis, it explains how and why something happened. So Analysis deals with something that has already happened in the past such as using the analysis to explain how a story ended or how there was a decrease in the sales last summer.
Now, talking about Analytics, it generally refers to the future instead of explaining past events. In other words, it explores potential future ones.
When we talk about Data Analysis, we call it a “detailed examination of data” (which must already exist). Since the data already exists, the data must pertain to something that happened in the past. As such, data analysis answers the question, “What happened?”
On the other hand, Data Analytics is defined as the “systematic computational analysis of data”. Hence, Data Analytics is further concerned about conducting logical, systematic, and deductive reasoning to provide insights for how to act in the future.