# Unstructured In general, unstructured data is information that is not arranged according to a pre-set data model or schema, and therefore cannot be stored in a traditional relational database or RDBMS. Similarly unstructured values are text data that has no patterns associated with it. It is like free text data and can be split into common and uncommon types. **Common types** Data that is common across verticals. Examples: first/last name , titles, comments, chat text, email text etc. **Telmai can offer:** Frequency analyzer to identify placeholders or over-represented data Statistical analysis of built-in features (length, spaces, tokens etc) Built-in validators, like names finder (Rosette) Language detection (separate data from different geographies) \[ for distant future] Tokenizer and NLP-based normalizer for attributes such as titles --- # 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://docs.telm.ai/academy/correctness/unstructured.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.