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The what and why of natural language processing search analytics and how it can help your business
The what and why of natural language processing search analytics and how it can help your business
If an enterprise is considering an advanced analytics solution, its IT and management teams may have done some research and analysis and concluded that it is designed to support business users. Augmented analytics was the right choice for it. But to democratize data, improve data literacy, and transform business users into citizen data scientist roles, enterprises must choose the right solutions and plan for business success.
Research firm Gartner has predicted that “natural language processing (NLP) search analysis technology improves productivity, user adoption, business results and market competitive positioning... 90% of corporate strategies will be clear Mention that information is a critical business asset and analysis is an essential capability."
If its competitors are implementing this strategy, then the business should do the same, but choose the right solution. In this case, one must first understand the concepts of new systems and solutions, and how data science and analytics are changing to incorporate search analytics, tools, and capabilities that support their business users.
Consider the ubiquity of Google searches and how the concepts of natural language processing (NLP) and tools that allow users to easily ask questions and get answers can be applied to business analytics for enterprises.
What is Search Analytics
One of the biggest barriers to self-service analytics is the need for a specialized set of skills to use the solution. The concept of search is to provide sophisticated functionality in a user-friendly environment so that users can leverage the tools to perform analysis and generate reports. Search analytics provides an interactive environment where business users can obtain fast and accurate results. These tools use natural language processing (NLP) to streamline input and output, allowing users to ask questions and receive answers without programming or analytics knowledge, increasing user adoption and the clarity and usefulness of enterprise-generated analytics and reports. Users can enter search queries using natural language instead of scrolling through menus and navigation or using drag and drop. The system translates this search analytics language query into an analytics platform that can interpret and return the most appropriate answer in an appropriate form, such as a visualization, table, number, or simple human language description.
Why Search Analytics
Search Analytics’ natural language processing (NLP) approach allows users to address questions in natural language. To answer questions, it provides relevant, easy-to-understand visual reports, numbers, trends and key performance indicators. Gone is the old structured approach, replaced by an expanded data environment where users can access information in a way that is meaningful to them and easy to interpret. Users can leverage these simple search analytics tools to perform analysis on any internal and external data source, laying the foundation for easily accessible fact-based data-driven analysis.
How Search Analytics Helps Business
Search analytics will produce clear results and the data is available in a smart adaptive user interface. Users can access these tools from a desktop, tablet, or mobile device, so users want to use the solution. Search Analytics further empowers businesses by helping them achieve rapid return on investment and maintain a low total cost of ownership with meaningful tools that are easy to understand and as familiar as Google search. These tools require minimal training to master and provide interactive tools that "speak the user's language." Search Analytics interprets natural language queries and presents results through intelligent visualizations and contextual information delivered in natural language, so every business user can take advantage of these tools, regardless of their skill level or analytical needs. When users can take advantage of this type of clickless analytical search functionality, they can get fast and clear results and use those results to solve problems, share information, and optimize business opportunities. With natural language processing-based search, users don’t have to scroll through menus and navigate. Businesses can solve complex problems using this simple search functionality and a scenario-flexible search mechanism that delivers one of the most flexible and in-depth search capabilities and results on the market today.
No-click analysis and scene search capabilities go beyond column-level filters and queries to provide more intelligent support. The solution translates scenario queries and returns results in the appropriate format, such as visualizations, tables, numbers, or descriptors. This natural language processing (NLP) search analytics technology improves productivity, user adoption, business results and competitive market position.
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