How can Haskell be used for data processing and analysis? Explain the relevant libraries and techniques.

Haskell is a powerful language for data processing and analysis, offering a rich ecosystem of libraries and techniques. Its functional programming paradigm, strong type system, and immutability make it well-suited for working with data in a concise and expressive manner. Let's explore how Haskell can be used for data processing and analysis, along with some relevant libraries and techniques. 1. Libraries for Data Processing and Analysis: * Data.List: The Data.List module provides a wide range of functions for manipulating lists, such as sorting, filtering, mapping, and folding. It offers powerful higher-order functions like `map`, `filter`, `foldr`, and `foldl'`, which enable concise and efficient data transformations. * Data.Text and Text: These libraries provide efficient and Unicode-aware string manipulation capabilities. They are particularly useful for handling large amounts of textual data, offering functions for parsing, encoding, decoding, and searching text. * Data.HashMap and Data.Map: These libraries offer efficient data structures for working with key-value pairs and associative arrays. They provide functions for insertion, deletion, lookup, and other operations, enabling efficient data aggregation and indexing. * Data.Vector: The Data.Vector....