Indexing in Azure Cognitive Search
The course is part of this learning path
This course will focus on the skills required to manage and maintain the indexing process for an Azure Cognitive Search solution. As data changes within a given data source, the requirement to rebuild an index or set up the schedule for an index becomes very important. Understanding all of the functions related to the indexing process is important when you know that there are going to be periodic updates to the underlying data source, and this course will teach you the skills to perform all of those functions.
- Manage re-indexing
- Rebuild indexes
- Schedule and monitor indexing
- Implement incremental indexing
- Manage concurrency
- Push data to an index
- Troubleshoot indexing for a pipeline
- Developers who will be including full-text search in their applications
- Data Engineers focused on providing better accessibility to organizational data
- AI Engineers who will be providing AI combined with search functionality in their solutions
Candidates for this course should have a strong understanding of data sources and the operational requirements for those data source changes. Candidates should also be able to use REST-based APIs and SDKs to build knowledge mining solutions on Azure.
Hi there, welcome to the Manage Indexing course here at Cloud Academy. My name is Brian Harrison, and I want to give you a introduction into this course, as well as myself, before we jump into the actual content and meat of the course. So, as I mentioned, my name is Brian Harrison, and I'm a cloud solution architect and had been working in the cloud industry primarily with AWS and Azure for more than a decade. And here's a couple of different ways that you can get in contact with me if you would like to reach out and stay in contact after viewing this course. Here's also an email address that you can use if you would like to contact Cloud Academy directly and provide either some feedback or you think some information should be changed.
Now, who exactly should be attending this course? First, developers who are gonna be including full tech search inside of their applications, data engineers who are focused on providing better accessibility to your organizational data in a consistent manner, and then lastly are AI engineers that are gonna be providing AI combined with full tech search functionality inside of their solutions.
Now, there are two primary course objectives to keep in mind here. This course is gonna focus on the skills required to manage and maintain the indexing process, which is the pushing of data or pulling of data into those indexes and then using that index inside of your Azure cognitive search solution. Secondly is understanding the functions related to the indexing process. They are important when you know that you're going to be periodically updating the underlying data source and this course is gonna teach you the skills to perform all of those functions.
Now, some of the prerequisites for this particular course, a candidate should have a strong understanding of data sources, both SQL and non-SQL and the operational requirements for those data source changes. Candidates should also be familiar with how to create an index and understand the basic concepts around the indexing process as this course is gonna dive much deeper into that understanding. And then candidates should also be able to use REST-based APIs and SDKs to build knowledge mining solutions. Some of the functions that are required in the more detailed functions around indexing do require that development level knowledge.
Now if you do have some feedback, and I mentioned this earlier, you can always send feedback directly to Cloud Academy via the email@example.com email address. Important, I am gonna be using screenshots and data that was current at the time of building this course. However, pricing fluctuates often. You should always check the latest pricing data when implementing your own solutions. And that also goes for any kind of other specific numbers or limits that I talk about with respect to search indexing.
Now the agenda for this particular course is gonna cover a number of deep topics around the indexing process. The first is diving deeper into how to get data into your index. Pushing, pulling, incremental indexing, all of that is gonna be covered. And then if you do need to update your index, whether it be a structural change or a non-structural change, how do you go about re-indexing or rebuilding an index when a major change has happened? We'll talk about how to schedule your indexing so that if you do need incremental indexing and you want to use an indexer, scheduling is gonna be one of the primary ways that that happens and we'll talk about how to make sure that that occurs. Managing concurrency, if you are going to be building indexes off of multiple data sources, or you're gonna be constantly interacting with numerous different objects or resources as part of your solution, how can you make sure that one of those resources hasn't changed? And then lastly, how can you monitor and troubleshoot your indexes to make sure that they're performing correctly, that you're not getting errors or that they're not taking too long to potentially perform their actual task? All of this is gonna be covered inside of this course. So let's start talking about these topics in the next video.
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.