Data Science

Exploratory Data Analysis

Data Science Process

For our clients, we transform raw data set into tidy form, analyze tidy data set, summarize and visualize key data characteristics. This helps our clients to get valuable insights and draw meaningful inferences. During exploratory data analysis, we specifically focuses on following aspects of the data;

  • Understanding characters
  • Identifying meaningful patterns, if there are any
  • Suggesting modeling strategies
  • Visualizing and interpretting key characteristics

EDA methods we apply include, but not limited, to the following:

  • Exploratory Data Plots
  • Dimensionality Reduction
  • Singular Value Decomposition (SVD)
  • K-means Clustering
  • Hierarchal Clustering


  • R
  • Excel
  • Python
  • Matlab