What are the differences between Data Processing, Data Preprocessing and Data Wrangling?
Data Processing
Data Processing is a mission of converting data from a given form to a more usable and desired form. To make it simple, making it more meaningful and informative. The output of this complete process can be in any desired form like graphs, videos, charts, tables, images and many more, depending on the task we are performing and the requirements of the machine.
Data Preprocessing
Data Preprocessing is a technique which is used to convert the raw data set into a clean data set. In other words, whenever the data is collected from different sources it is collected in raw format which is not feasible for the analysis.
Hence, certain steps are followed and executed in order to convert the data into a small and clean data set. These set of steps is known as Data Preprocessing. The Data Preprocessing steps are:
- Data Cleaning
- Data Integration
- Data Transformation
- Data Reduction
- Data Wrangling
Data Wrangling
Data Wrangling is a technique which is performed at the time of making an interactive model. In other words, it is used to convert the raw data into the format convenient for the consumption of data.
Data Wrangling technique is also known as Data Munging. This method also follows certain steps like after extracting the data from different data sources, sorts the data using particular algorithm is performed, decomposes the data into a different structured format and finally stores the data into another database.
