Having a large repository of data is a huge plus. However, it is the art of turning that data into information is what matters for efficient business. The main obstacle in front of you to achieving this is the sheer quantity of data you would go through. Even using a search function through unstructured data can yield mixed results, making data that you do have seem lost. This is where Amazon Kendra comes in and makes the search experience much more refined using machine learning.
This highly scalable AWS service makes enterprise-level search accessible and accurate, almost as if you were consulting an expert. You can use it to ask specific questions relating to, or simply search for, data that you need.
You can use Amazon Kendra to ask fact-based questions, as long as the exact answer is available in the database. These include the who, what, when, and where of any given situation that you might need.
Descriptive questions are also supported, these can be instructional how-tos or something else entirely. Answers are returned in the form of sentences, paragraphs, or even entire documents in cases where it makes sense.
For questions where you don’t need a definitive answer, but just information, you can use a simple keyword search. Just simply plug in the search term and you will be granted access to any information on the topic. These can be in any form from your repository as long as it is relevant, like files, documents, or excerpts.
AWS machine learning models make sure that the relevance of such queries is on point. Access to all of your unstructured data will give it ample opportunity to learn about your needs while being secure.
Besides just using keywords to find similar results, Kendra goes deeper into the context of the content for more relevance. By understanding both the user question and the content in data, it can deliver results as if they were found by a person, at a fraction of the time and cost. It uses natural language processing to analyse your data to return the matching content, even if it’s a text snippet. This allows it to retrieve the information from wherever it resides in the organisation’s database.
Over time, because of the nature of machine learning, results will actually start getting better.
With Kendra, you can connect your own repositories from various database sources. These include Amazon’s own S3 and RDS, along with Sharepoint, ServiceNow, and Salesforce. With these in tandem, you can search on an enterprise level with all of your data for the best results.
Access documents stored in third-party services as well to make sure no stone is left unturned.
Modern search platforms and solutions often have an in-depth setup involving a lot of preference settings. With Kendra however, machine learning will set your preferences for you. The service will actually learn from you over time instead of staying the same way forever.
All you have to do is configure an index for your sources, and Kendra will begin searching.
Besides just learning from your data and search patterns, Kendra’s models have an understanding of 14 industry domains to begin with. You can optimize it further by adjusting the importance of data sources, authors, newness, or using custom tags.
You have complete control over who has the ability to access the Kendra search console. The secure enterprise search delivers through the security model it develops in your organization. Customers become responsible for the authentication and authorisation of users who gain access to the search application.
When you have search capabilities like you would with Kendra, it removes a world of bottlenecks that you come across. Business processes become more accessible while you have a better way to search for your own assets.
When you start using machine learning, both you and your data will start learning from each other. You will start to feel the automation it creates when it comes to search processes so you won’t ever feel you don’t have access to something that should be there.
Get Amazon Kendra now and start searching for success!
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