The importance and existence of data visualization should be discussed in a visualization lifecycle. There are different steps involved in a visualization lifecycle, these are source of the data, database, data filtering, and generating visuals:
Source of the data: A huge volume of data can be generated from different sources, such as retail stores, social media, financial sectors, and so on.
Database: We can dump the data in databases. There are different database types available, such as XML, JSON, CSV, MY SQL, and so on.
Data filtering: First, we have to check the data type, the structure of the data, and how many columns the data stores. Then, we can go for data filtering using parsing, filtering, aggregation, and cleansing, and for normalization methods if required, to get structured data. Afterward, we can generate a common output format for visualization tools (e.g. CSV).
After getting the structured data or contextual data, we can apply visualization tools...