A novice may think that once we complete collecting data and it is imported into Google Cloud, it is finally time to start the analysis process. Conversely, we must first proceed with the preparation of data (data wrangling).
Data wrangling is the process of the transformation and mapping of data, turning raw data into formatted data, with the intent of making it more appropriate for subsequent analysis operations.
This process can take a long time and it is very cumbersome, in some cases taking up about 80 percent of the entire data analysis process.
However, it is a fundamental prerequisite for the rest of the data analysis workflow; so it is essential to acquire the best practices in such techniques. Before submitting our data to any machine learning algorithm, we must be able to evaluate the quality and accuracy of our observations. If we do not know how to switch from raw data to something that can be analyzed, we cannot go ahead.