Difference between Data Science and Operations Research
1. Data Science :
It’s a set of methodologies of taking thousands of forms of data that are available to us today and using them to draw meaningful conclusions. Data is being collected all around us, every like, click, email, credit card swipe, or tweet is a new piece of data that can better describe the present or better predict the future.
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In data science we generally have four steps to complete any project :
Data Collection :
First, we collect data through different ways like surveys, geo-tagged social-media posts, web-traffic results, financial transactions, etc. Once collected, we stored it in a safe and accessible way.
Data Prediction :
Now, data is in raw form so the next step is to prepare data, this includes cleaning data, for example, finding missing or duplicate values, or converting data into a more organized form.
Exploration and Visualization :
Then we explore and visualize the data, this could involve building a dashboard, track how the data changes over time, or performing comparisons between two data sets.
Experimentation and prediction :
Finally, we run experiments and predictions on the data for example finding which webpage requires more customers.
2. Operation Research :
Operation Research is a scientific approach that deals with the application of advanced analytical methods to help make better decisions or conclusions. Using techniques from the mathematical sciences like statistical analysis, mathematical optimization, mathematical modeling, Operation Research arrives at the solution of complex decision-making problems. It is normally carried out by teams of scientists and engineers drawn from a variety of disciplines. Operations research is not a science itself but rather the application of science to the solution of managerial and administrative problems.
Difference between Data Science and Operation Research : Sno. Data Science Operations Research
1. Data Science uses data to derive insights out of the data. Operation Research is an analytical method of problem-solving and decision-making that is useful for Business management. 2. Data involved here might be unstructured or semi-structured. The data involves here is mostly structured. 3. Programming and Coding are involved. No Coding is involved here. 4. Studies patterns in data to predict future possibilities. The goal is to find the best possible solution to a question. 5. Commonly used across in e-commerce, finance, and study sector. Use across scheduling and time management, Inventory management, risk management, etc. 6. Advanced data science involves the application of artificial intelligence and machine learning. Involves the application of Optimization, Simulation, Probability, and statistics which are also its characteristics.
These terms may sound similar to each other but both have different work. Since both the terms require data and works on data, people became confused between the two. Operation research is a scientific approach to solve problems using mathematical sciences while data science is used to visualize the present and predict the future using data.