Here is a list of top 5 data analytics methodologies which can be used to solve different business problems and in a way create business value for any organization:
- Optimization: Simply speaking, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values (also termed as decision variables) from within an allowed set and computing the value of the function. An optimization problem consists of three things: A. Objective function B. Decision variables C. Constraint functions (this is optional)
- Linear / Non-linear programming with constrained / unconstrained optimization
- Linear programming with constrained optimization
- Objective function and one or more constraint functions are linear with decision variables as continuous variables
- Linear programming with unconstrained optimization
- Objective function is linear function with decision variables as continuous variables
- Non-linear programming with constrained optimization
- Objective function is non-linear with one or more constraint functions with decision variables as continuous variables
- Non-linear programming with unconstrained optimization
- Objective function is non-linear but there are no constraint functions
- Linear programming with constrained optimization
- Multi-objective optimization: There can be multiple objective functions in case of multi-objective optimization
- Ant colony optimization
- Evolution strategies
- Linear / Non-linear programming with constrained / unconstrained optimization
- Predictive Analytics: Predictive analytics is about predicting something using different techniques such as the following:
- Machine learning / Deep learning
- Natural language processing
- Time-series forecasting
- Fuzzy modeling
- Genetic programming
- Agent based modeling
References
- Evolution strategies as an alternative to reinforcement learning
- Mathematical optimization
- Ant colony optimization
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I found it very helpful. However the differences are not too understandable for me