Introduction
Searching for information online has never been easier. However, it's still a challenge to find information from documents that aren't in a search index. For example, every day, people deal with unstructured, typed, image-based, or hand-written documents. Often, people must manually read through these documents to extract and record their insights in order to persist the found data. Now we have solutions that can automate information extraction.
Knowledge mining is the term used to describe solutions that involve extracting information from large volumes of often unstructured data. One of these knowledge mining solutions is Azure AI Search, a cloud search service that has tools for building user-managed indexes. The indexes can be used for internal only use, or to enable searchable content on public-facing internet assets.
Importantly, Azure AI Search can utilize the built-in capabilities of Azure AI services such as image processing, content extraction, and natural language processing to perform knowledge mining of documents. The product's AI capabilities makes it possible to index previously unsearchable documents and to extract and surface insights from large amounts of data quickly.
Learning objectives
In this module, you will:
- Understand how Azure AI Search uses cognitive skills
- Learn how indexers automate data ingestion steps, including JSON serialization
- Describe the purpose of a knowledge store
- Build and query a search index