What is Data Wrangling in Data Analysis?
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Data Wrangling, regularly referred to as Data Munging, is a central step in the data analytic process. It contains transforming raw data into a more digestible and usable format for analysis.
This process includes cleaning, structuring, and educational data to security its quality and effectiveness.
Data Wrangling includes several tasks: detecting and addressing missing values, correcting variations, restructuring and collecting data, and combining datasets from various sources. By doing so, it prepares the data for understanding analysis and decision-making.
Active Data Wrangling leads to reliable datasets that are important for correct analytics, predictive modeling, and data-driven approaches.
It’s a combination of art and science, demanding both technical skill and domain knowledge to produce meaningful results.
Written By - Koushal Soni.
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