MCDM Techniques for Professional Data Analysis

I have a dataset that I want to analyze in a professional and structured way using Multi-Criteria Decision-Making (MCDM) techniques. My goal is to select the most appropriate technique(s) based on the nature of my data and research objectives. I am considering 25 well-established MCDM methods, which include:

Analytic Hierarchy Process (AHP)

Analytic Network Process (ANP)

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)

VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR)

Elimination and Choice Expressing the Reality (ELECTRE)

Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE)

Simple Additive Weighting (SAW)

Weighted Aggregated Sum Product Assessment (WASPAS)

Complex Proportional Assessment (COPRAS)

Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

Extended MOORA (MULTIMOORA)

Additive Ratio Assessment (ARAS)

Multi-Attribute Utility Theory (MAUT)

Simple Multi-Attribute Rating Technique (SMART)

Decision Making Trial and Evaluation Laboratory (DEMATEL)

Best-Worst Method (BWM)

Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH)

Utility Additive Method (UTASTAR)

Grey Relational Analysis (GRA)

Fuzzy Analytic Hierarchy Process (Fuzzy AHP)

Fuzzy TOPSIS

Fuzzy VIKOR

Step-wise Weight Assessment Ratio Analysis (SWARA)

TODIM (an interactive and multicriteria method based on prospect theory)

Rough Set-based MCDM techniques (e.g., Rough AHP, Rough TOPSIS, Rough VIKOR)

I am looking to proceed with a technique or combination of techniques that best fits the characteristics of my data and decision problem.and writing the result and analysis