The What and Why of NLP Search Analytics and How It Can Help Your Business
This article defines Search Analytics, the WHAT and WHY, and the BENEFITS of implementing this solution.
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If your business is considering an advanced analytics solution, your IT and management team has probably already done some research and concluded that the concept of augmented analytics designed to support business users is the right way to go. However, to democratize data, improve data literacy, and transition business users to the Citizen Data Scientist role, the business must select the right solution and plan for success.
'NLP search analytics technology improves productivity, user adoption, business results and competitive positioning in the market.'
Gartner, the renowned technology research firm, has predicted that '… 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.' Your competitors are implementing this strategy, and it is time you do so as well. But suppose you are to choose the right solution. In that case, you must first understand the concepts of new systems and solutions and how data science and analytics have changed to incorporate search analytics, tools, and features that will support your business users.
Consider the ubiquitous nature of Google-type searches and how the concept of natural language processing (NLP) and tools that allow users to ask questions and get answers easily can be applied to your business analytics.
This article defines Search Analytics, the WHAT and WHY, and the BENEFITS of implementing this type of solution.
One of the greatest obstacles to self-serve analytics is needing a specialized skill set to use the solution. The concept of search is designed to provide sophisticated features in a user-friendly environment so business users can leverage these tools to perform analysis and produce reports. Search analytics offers an interactive environment wherein business users can obtain rapid, accurate results. These tools use natural language processing (NLP) to simplify the input and output so that users can ask questions and receive answers without programming or analytical knowledge, thereby enhancing user adoption and the clarity and usefulness of the analysis and report the enterprise produces. Rather than scrolling through menus and navigation or using drag and drop, the user can enter a search query in natural language. The system translates that search analytics language query into a query that the analytics platform can interpret and return the most appropriate answer in an appropriate form such as visualization, tables, numbers, or descriptions in simple human language.
The natural language processing (NLP) approach to Search Analytics allows users to process questions in natural language. To answer questions, it presents relevant easy-to-understand visualization reports, numbers, trends, and key performance indicators (KPIs). The old, structured approach is gone, replaced by an expanded data environment where users can get information in a way that is meaningful to them and easy to interpret. Users can leverage these simple Search Analytics tools to perform analytics on any internal and external data sources, thereby creating a foundation for fact-based, data-driven analysis that is easily accessible.
How It Can Help Your Business
Search analytics produces clear results, and data is available in an intelligent adaptive user interface. Users can access these tools from any desktop, tablet, or mobile device, so users will WANT to use the solution. Search Analytics further supports your business by helping you achieve rapid ROI and sustain a low total cost of ownership (TCO) with meaningful tools that are easy to understand and as familiar as a Google search. These tools require very little training and provide interactive tools that 'speak the language' of the user. Search analytics interprets natural language queries and presents results through smart visualization and contextual information delivered in natural language so every business user can capitalize on these tools, regardless of their skill level or analytical need. When a business user can leverage this type of clickless analytics search capability, the user can achieve rapid, clear results and use those results to solve problems, share information, and optimize opportunities for the business. Users do not need to scroll through menus and navigation with natural language-processing-based search capability. Instead, the business can address complex questions using this simple search capability with a contextual flexible search mechanism that provides one of the most flexible, in-depth search capabilities and results in today's markets. Clickless Analysis and contextual search capabilities go beyond column-level filters and queries to provide more intelligence support. The solution translates the contextual query and returns results in an appropriate format, e.g., visualization, tables, numbers, or descriptors. This NLP search analytics technology improves productivity, user adoption, business results, and competitive positioning in the market.
'You must understand how data science and analytics have changed to incorporate search analytics, tools, and features that will support your business users.'
Published at DZone with permission of Kartik Patel. See the original article here.
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