# Data Profiling Data Profiling is the process of familiarizing oneself with the data. Data Familiarization/Profiling is needed because: * Data may come from multiple sources * The meaning of the data/attributes may not be evident * Sufficient effort and interaction with subject matter experts may be needed to understand the meaning of the data/attributes in the data It is also important to ensure data quality before attempting to create a visualization. Some quality issues include erroneous values, values with wrong types, missing values etc. The process of transforming poor quality data into usable data is called **data wrangling**. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://vikram-bajaj.gitbook.io/cs-gy-6313-information-visualization/data-abstraction-and-transformation/data-profiling.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.