Artificial intelligence is driving digital transformation at an impressive speed in all types of organizations, allowing companies to focus on their business and customer relationships in entirely new ways. But there is one area in particular, unexplored by many, that allows individuals and companies to build key solutions for their digital infrastructures. This is cognitive research. Let's see how Microsoft is implementing this new technology to increase the productivity of companies by exploiting one of their main assets: information.
Azure Cognitive Search of Microsoft Azure is a cloud-based search service (Search as a Service) that provides programmers with the infrastructure, APIs and tools necessary to create advanced search experiences from private and heterogeneous data collections and then exploit them in web applications, mobile apps and business solutions.
And that's not all, despite being a complete service in itself, companies still have the opportunity to create customized solutions integrating their data management models. In addition, as with all Azure products and services, the powerful security and privacy infrastructure offered by Microsoft is available to users, which helps to protect information both of the company and of the customers themselves.
There is an indisputable reality in today's world, and that is that we generate more and more data and information with each passing day. Recent estimates indicate that the world creates more than 2.5 quintillion bytes of data every day. An impressive figure in itself but that is, ironically, not even the biggest problem with this particular situation.
So let's introduce a problem that database managers will probably already know (and have learned to hate), namely that information usually comes in “unstructured” formats: PDFs, images, videos, audio files and PowerPoint presentations, just to name a few.
It is estimated that around 80% of the world's business data is unstructured or semi-structured.
The result is that taking advantage of this information can cost a company a lot of time and money. As a result, decisions are often less informed and take longer to make, and the work is done manually, based on intuition. We are unable to find the content, using tools and applications that can very often even hinder the user experience.
In the end, our information has the potential to become an advantage or a burden, depending on how it's used. So we all face a similar challenge: how do we apply our information meaningfully to our products and business?
Computer science is constantly being renewed and today concrete innovations in vision, voice, language, knowledge and research itself allow for the first time our applications to interpret unstructured data in a human-like way, and to understand traditional data in text form even more deeply, so that when research operations are combined with artificial intelligence, together they allow us to create solutions capable of finding more value in data.
This translates into engaging customers, transforming products, empowering employees, and improving business operations. Azure Cognitive Search can help us with exactly that. Let's see how.
First of all, the use of Azure Cognitive Search involves organizing data in a structured way and indexing them so that they can be easily searched by users. The service provides two different indexing engines: the technology of natural language processing (Natural Language Processing or NLP) owned by Microsoft or the analysers of the open source libraries of Apache Lucene. Microsoft's search engine is built on the Elasticsearch model.
If you are indexing, for example, text documents, Azure Cognitive Search will analyze the content of each document and will create an index that associates the keywords with the documents. This index will allow Azure Cognitive Search to quickly find documents that match certain search queries.
Once the data is indexed, users will be able to search using specific keywords or phrases. When a user enters a search query, Azure Cognitive Search will review the data index to find matches between the keywords and the previously indexed data.
The results will be ranked by Cognitive Search based on their relevance. There are several factors to determine the relevance of a result, such as the frequency of keywords in the document or their position in it.
What sets Azure Cognitive Search apart is the incorporation of Artificial Intelligence capabilities in order to vastly improve search functionality.
The service can use the optical character recognition (OCR) to extract text from scanned images or documents without the need for additional intervention. The use of machine learning algorithms it also allows Cognitive Search to understand the meaning of the text and gives users the opportunity to find information even if a document does not contain exactly the keyword they were looking for.
Azure Cognitive Search could therefore still find the information we want to obtain taking into account the contextual proximity to the topic searched, the synonyms of the keywords used in the indexed results and other discriminating criteria to narrow down the relevant results without sacrificing tangentiality and potentially significant correlations.
Consider how revolutionary the ability to interpret audio recordings, images and texts themselves can be so that, in order to find specific content, semantic searches can be applied to exploit the existence of synonyms in order to find a particular document, or start searches regardless of the language that originates the query or the language in which the documents were written.
It should also be noted that from October 2023, the integration of Azure Cognitive Search functionality with Sharepoint is available in preview, which allows companies to enhance search capabilities within Sharepoint by exploiting the advanced features of Azure Cognitive Search, which can now connect to the app's sites and libraries to index content such as documents, lists and other types of data present within it.
By integrating Cognitive Search Azure with SharePoint, organizations can now create a unified search experience across all of their content repositories, including SharePoint sites, external databases, and other data sources.
Given a general overview of how Azure Cognitive Search works, someone might wonder what the difference is between the latter and Azure Search, the previous search service offered by the Azure platform. In a nutshell: basically none. Azure Cognitive Search is the sum of previous features offered by Azure Search together with new cognitive services implemented by Microsoft in its research service.
Let's briefly clarify the situation: Azure Search is now called Azure Cognitive Search because Microsoft renamed it in October 2019. The choice was made by the Redwood company to reflect the implementation and expanded (although optional) use of cognitive abilities and AI processing in the operations of the new Azure family business service. In doing so, it offered powerful indexing capabilities so that programmers could create unique solutions with which to exploit and find value in all types of data.
As a result, the versions of the APIs, NuGet packages, namespaces and connection points that we already had with Azure Search could have remained unchanged, to the relief of the technical community, since both the new and existing search solutions would not have been affected by the change of name of the service.
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Azure Cognitive Search of Microsoft Azure can be applied in different key scenarios, depending on what you are trying to do with the information that we already have or that we might find ourselves managing. Let's see together what are the advantages that customers and companies can derive from its implementation in some common use cases.
The features of Azure Cognitive Search allow, as we have already seen, to propose the most relevant information for your customers on a website or an application. This can significantly increase sales and customer satisfaction, in addition to greatly improving the overall user experience by providing simple, fast and accurate search tools.
Un e-commerce website would have the option of implementing a search function that allows users to quickly find the desired products using keywords, filters and other advanced search options. Un News portal, using Azure Cognitive Search, could take advantage of a recommendation system that suggests relevant articles to users based on their interests and their previous interactions.
Or again in amobile app for customer support an intelligent search function could be implemented that understands the natural language of users and returns relevant and detailed answers, giving users the opportunity to solve their problems quickly and with step-by-step solutions.
Azure Cognitive Search allows you to search for information in isolated data sources, with different filing systems and file types. A company that manages data from different business management systems, such as CRM, ERP, and internal databases could index and search for this data quickly and efficiently, regardless of its origin or format.
As we've already mentioned above, crucial information is often packed into unstructured documents such as PDFs, text documents, and presentations. Azure Cognitive Search allows you to index and search the content of these documents, allowing users to quickly find the information they need.
Cognitive Search can also be used to search for information from external sources, such as RSS feeds, social media data or web services, a very useful feature for a company to monitor industry trends, search for mentions of its brand on social media or analyze customer reviews to identify possible areas for improvement.
With Azure Cognitive Search, we can facilitate the linking and grouping of fragmented information, allowing a unified and organized view of the data.
A company committed to manage data from different departments and management systems using Cognitive Search you can index and link this data into a single search platform. Customer data from Customer Relationship Management can be linked to sales data from the ERP (Enterprise Resource Planning) system, giving a complete view of the customer's life cycle and ensuring that the company can make more informed decisions on marketing plans and sales strategies.
Azure Cognitive Search also allows you to group related information to make it more accessible and useful for users. You could use the search to group related products based on user preferences or past purchases, allowing them to quickly find what they are looking for and increase sales through personalized recommendations.
The service minimizes the duplicating data. For example, instead of keeping separate copies of customer data in different systems, it is possible to link this data into a single research platform, minimizing the complexity and costs associated with managing the data and ensuring the consistency and accuracy of the information provided.
Azure Cognitive Search allows a more accurate classification of data, improving the management and use of business information.
Take for example a large set of business documents, some of which are confidential and others are public.
With Azure Cognitive Search, we can implement an automatic classification system for documents based on their content and the sensitivity of the information that automatically identifies documents that contain personal or confidential information, assigning them a corresponding classification label that allows us to better manage and protect sensitive data and comply with privacy regulations.
Finally, with Azure Cognitive Search, we can implement a data analysis system which allows us to better understand our business and identify unique patterns. We can analyze sales data to identify emerging market trends or identify underserved customer segments and take a proactive approach to improve our marketing strategies and maximize growth opportunities.
The service also gives the possibility to implement a customized alert system which can provide us with timely information on anomalies, unusual patterns and automatically detect significant deviations from historical models. For example, we may be notified when the number of visits to our website exceeds a certain threshold or when unexpected traffic peaks occur or, in the event of malfunctions, to intervene quickly to resolve any technical problems.
These are just a few examples of how it is possible to implement Cognitive Search Azure but the ability to take advantage of it is, to use a very often inflated term, almost unlimited.
The Azure Cognitive Search pricing system adopts a based payment model on actual use of the service and the rates vary from one first level free to paid versions of varying cost as you decide to take advantage of the most advanced features. The first free level is a great tool for working on prototypes for our applications, but not recommended for production applications.
If you have a certain amount of data to store or a certain number of indexes you need, you may need to upgrade to more expensive levels. So you need to plan your indexed data sources carefully, or the amount of data sources could quickly push you toward more expensive usage plans before the storage limit does.
It would be advisable to first consolidate the data to be indexed. A single source tends to be significantly cheaper in Azure Cognitive Search than any number of different sources that may increase over time.
This consolidation may take different forms depending on the architecture of the application we are working on, but it can commonly translate into the use of a single storage account to store different types of information or the involvement of some type of process (manual or automated) to collect things from different systems and place them in a single location where Cognitive Search can find them.
The information we enter on Azure for indexing is subject to storage costs. If we want to index a storage account, we will still have to pay for the archived items based on their frequency of use and the type of storage. Storage costs generally tend to increase over time as the volume of data stored increases.
Configuring cognitive search competence with custom entities involves an additional cost based on the amount of records indexed with this function.
Even the function of”document cracking“for image-based documents, there is a small additional cost. This feature is often a key contribution for people who use Azure Cognitive Search, so it should be considered less as a cost to avoid and more as the real basic cost of the service.
Regarding the functionality of semantic search, aimed at improving results also considering terms that are semantically identical to those searched, this is free for paid Cognitive Search plans that use low-volume scenarios (less than 1,000 queries per month) but involves an additional cost based on excess usage depending on the edition of Cognitive Search being used.
Finally, it should also be borne in mind the possible application of secondary costs for functionalities such as Security Center or backup, depending on the type of service used to store our data and the policies applied to your account.
As with any other Azure service, we would like to point out the possibility of using the convenient calculation tool offered by Microsoft (which you can find hither) to estimate the specific costs for your company based on geographical area, currency used for payment and length of use of each of the services that can be used (calculated by hours or by months) and find the most suitable employment solution for your needs.
To conclude our overview, we can state without particular problems that Azure Cognitive Search presents itself as a powerful and economic solution for indexing a wide variety of sources of information and adding additional context to the search results in the form of extensible skills.
A tool with many possibilities and an extremely competitive price that can be a real game changer for all those companies that need to exploit their information to the maximum of their potential.
We therefore invite you to test the free plan for yourself to get a taste of the features of Azure Cognitive Search and what it can do for your company.
Azure Cognitive Search is a cloud-based search service from Microsoft Azure that allows developers to integrate advanced search capabilities into their applications. It provides features like full-text search, filtering, and faceting, along with AI-powered search enhancements like natural language processing and image recognition.
Azure Cognitive Search enhances search functionality by leveraging AI-driven algorithms to understand and process content more intelligently. It offers features such as semantic search, cognitive skills for content enrichment, and the ability to index and search unstructured data, improving the relevance and accuracy of search results.
The key features of Azure Cognitive Search include full-text search, filtering, faceting, autosuggest, and AI-powered capabilities like natural language processing, image analysis, and entity recognition. It also supports geospatial search and the integration of custom analyzers and cognitive skills.
Yes, Azure Cognitive Search can be used with unstructured data. It allows you to index and search various types of content, including text, images, and documents, making it easier to extract meaningful insights from unstructured data sources.
Cognitive skills in Azure Cognitive Search are used to extract and enrich data during indexing. These skills apply AI capabilities like image recognition, sentiment analysis, and language detection to transform raw content into searchable information, improving the quality and relevance of search results.
You can integrate Azure Cognitive Search into your application by using its REST API or SDKs available in multiple programming languages. The service can be customized to fit specific search requirements, and it supports integration with various data sources, such as Azure Blob Storage and Cosmos DB.
Yes, Azure Cognitive Search is highly scalable. It can handle a wide range of workloads, from small applications to large-scale enterprise solutions. The service allows you to adjust resources based on demand, ensuring optimal performance and cost-efficiency.
Azure Cognitive Search offers robust security features, including role-based access control (RBAC), encryption at rest and in transit, and integration with Azure Active Directory (AAD) for authentication. It ensures that data is protected throughout the search process.
Yes, Azure Cognitive Search supports multi-language search. It includes built-in language analyzers and stemming algorithms for various languages, enabling the service to handle multilingual content effectively and return relevant search results across different languages.
Common use cases for Azure Cognitive Search include enterprise search, e-commerce site search, knowledge management, and application search. It is used to provide fast and accurate search results, improve content discoverability, and enhance user experiences across various industries.
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