October 7, 2022

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If your business is focused on data-driven, fact-based decisions, your business users can take advantage of an analytics solution to collect, discover, and analyze data. Business goals include improving results and productivity and getting the best results out of your data, as well as gaining meaningful insights into the data. But, you definitely want to accomplish all of those goals without frustrating business users or forcing them to adopt tools that don’t add value to their day-to-day workflow and tasks.

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When a business sets goals and establishes metrics to determine the value of an analytical solution and a business user analysis initiative within the enterprise, the management team often fails to focus on the more subtle but powerful concept of efficacy. Is. How effective is the search process and just as important, the results generated from that search. If a user can quickly and easily ask a query without having to search and select a column or field, they can avoid the time and complexity of putting together an effective search and the frustration of finding results tailored to their needs.

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When a business envisions a data-driven environment and establishes a foundation with an analytical solution, it should expect user adoption and a more data-literate team environment. But, without effective search tools, that vision will fall short.

Augmented analytics that includes context-driven natural language processing (NLP) will provide your business with the support it needs to achieve the results you expect.

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Context-driven search using Natural Language Processing (NLP) allows users to go beyond restrictive search based on column filters to provide context, such as season, time series or range, and polarity, and they can use abbreviations Addresses and analyzes phonetics to handle misspellings. This approach allows users to ask a question using a more human, conversational approach, without having to consider what columns or fields they need or how to ask the question without frustrating the user to receive an answer. Without his question provides meaningful insight. Or results that have nothing to do with the question.

To understand the true value of this type of device, it is helpful to consider a few examples of business applications.

Context: Time Series Advantage: Enter a query and get results based on absolute time, or by a range or relative time period. Sample Date Range Question: Which sales rep sold the most pancake mix during April 2015 to May 2019? Sample Relative Time Period Question: Who sold the most cakes in Phoenix, Arizona in the last quarter of 2019? Sample Absolute Time Question: What is Bill Jones’ best-selling product for this year? Context: Synonyms, Phonetics and Abbreviations Advantages: Enter the question and the system will recognize and process the correct information for spelling errors, abbreviations and related words. Sample Phonetics-Based Question: Who sold the most fruit juice in Phoenix, Arizona at Christmas of 2018? Sample abbreviation Question: Who sold the most fruit juice at Phoenix Age at Christmas 2018? Context: Aggregation Gain: Enter a query to understand the results of Average, Min, Max, First, Last, Sum, Count, etc. Sample Average Question: What is the average list price for ginger tea in the Western Region? Sample Count Question: Tell me the number of sales representatives in Arizona.

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Think of context-driven search as the basis for greater collaboration and better insight. If you are sitting in a staff meeting or at a conference, and are listening to a presentation, the presenter will often provide time for questions at the end of the session. After considering the topics and issues presented, you may need answers to further clarify the information you are processing and to make the best use of the information presented. Context-finding provides the same kind of support.

If a sales manager is considering how to optimize his sales team and leverage customer product and purchasing preferences, the business will want to encourage creativity and out-of-the-box thinking. With context-driven search, the sales manager can ask all kinds of questions to test theories and hypotheses. She can explore team results and discover interesting and useful insights into sales, territories, team versus individual results and more – all without understanding data extraction techniques or using column filters and other data structural components that are complex. To search or navigate. Menu or script to get answers from data. What you want (and what you will get) from NLP searches is the do-it-yourself approach to searching. Think of a question and type that question and you will get the results.

When a business is choosing analytical tools, it is wise to choose tools that support how humans think and communicate and that clearly provide results to support fact-based decisions. Keep it as simple as possible. Ask a question and get an answer. This is the most efficient way to find information.

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