Implementing an Azure Cognitive Search Solution
This lesson focuses on the skills necessary to implement a knowledge-mining solution with a focus on the Cognitive Search solution. The lesson will walk through how to create a Cognitive Search solution and how to set up the process for importing data. Once the data sources have been set up properly, the lesson will teach you how to create a search index and then how to configure it to provide the best results possible.
Learning Objectives
- Create a Cognitive Search solution
- Import from data sources
- Create, configure, and test indexes
- Configure AutoComplete and AutoSuggest
- Improve results based on relevance
- Implement synonyms
Intended Audience
- Developers who want to include full-text search in their applications
- Data engineers focused on providing better accessibility to organizational data
- AI engineers that provide AI combined with search functionality in their solutions
Prerequisites
To get the most out of this lesson, you should:
- Have a strong understanding of data sources and how data will be needed by users consuming a Cognitive Search solution
- Be able to use REST-based APIs and SDKs to build knowledge-mining solutions on Azure
Resources
Brian has been working in the Cloud space for more than a decade as both a Cloud Architect and Cloud Engineer. He has experience building Application Development, Infrastructure, and AI-based architectures using many different OSS and Non-OSS based technologies. In addition to his work at Cloud Academy, he is always trying to educate customers about how to get started in the cloud with his many blogs and videos. He is currently working as a Lead Azure Engineer in the Public Sector space.