To make sure that we get the required outcome from the data, we must collect the right and relevant data.
It is essential to have correct and good quality data to make an analysis or to construct algorithms that can have an impact. Without relevant data, your analyses will not only be irrelevant, but they can also be misleading.
You cannot expect to find perfectly preprocessed raw data that be used directly for your needs. Hence, you need to understand how the data was gathered and what sources it was collected from.
Therefore, it is essential to understand how to collect relevant data for analysis.
Let us understand what steps we need to take to make sure that we collect the right set of data for analysis.
Quality of the Data - Primary and most vital point to consider while collecting the data is the quality of data that is getting collected. If we collect incomplete data, build an unreliable database, and run analysis on skewed data sets, obviously we are not going to arrive at the required output. The quality of data that is collected should always be the top priority while assessing the data.
Completeness of data - We need to make sure that the data that is getting collected is a complete set. Incomplete sets of data may cause many discrepancies and wrong output on analysis.
Format of data - The format of the Data that is collected for analysis should be right. Data should be accessible and readable for analysis. If the collected data is not in the right format, we should convert it to the required format for analysis.
