I have already completed the data-gathering phase for my thesis, “Digital Transformation in Reshaping MSME’s Liquidity Strategy,” and I now need focused help with the data analysis itself. My goal is to extract clear, academically rigorous insights that demonstrate how digital transformation tools and processes influence liquidity decisions within micro, small, and medium-sized enterprises. Here’s what I’m looking for: • A researcher who is comfortable diving straight into an existing dataset and choosing the most appropriate analytical techniques (regression, factor analysis, thematic coding—whatever best fits the data). • Clean, well-documented output that I can slot directly into my methodology and findings chapters—tables, charts, interpretation, and concise explanations of statistical significance. • Guidance on how to frame the results so they align with current literature on MSME finance and digital transformation. I’ll share the raw data, my preliminary hypotheses, and any institutional guidelines the moment we begin. If you prefer specific tools—SPSS, R, Stata, Python’s pandas/scikit-learn, or NVivo for qualitative strands—just let me know; I’m flexible as long as the final analysis is transparent and replicable. Please reach me on +91 86670 67980 for a quick discussion, and let’s move this project toward a solid, publishable conclusion.