There are four key types of business analytics: descriptive, predictive, diagnostic, and prescriptive. Descriptive analytics is the interpretation of historical data to identify trends and patterns, while predictive analytics centers on taking that information and using it to forecast future outcomes. Diagnostic analytics can be used to identify the root cause of a problem. In the case of prescriptive analytics, testing and other techniques are employed to determine which outcome will yield the best result in a given scenario.
Across industries, these data-driven approaches have been employed by professionals to make informed business decisions and attain organizational success.
Business Analytics vs. Data Science
It’s important to highlight the difference between data analytics and data science. While Both processes use big data to solve business problems they’re separate fields.
The main goal of business analytics is to extract meaningful insights from data to guide organizational decisions, while data science is focused on turning raw data into meaningful conclusions through using algorithms and statistical models. Business analysts participate in tasks such as budgeting, forecasting, and product development, while data scientists focus on data wrangling, programming, and statistical modeling.
While they consist of different functions and processes, business analytics and data science are both vital to today’s organizations. Here are four examples of how organizations are using business analytics to their benefit.
