Business users are business professionals who have expertise in an industry or market area or perform a task to support the ongoing operation of the business – professionals who may be front-line workers on a production line, finance professionals, sales Representatives, nonprofit office workers, medical researchers, middle managers, regional managers for retail chains, transportation dispatchers, or… well, you get the idea. These team members know their job and they do it well. But they probably don’t have the technical skills to write SQL queries, or filter columns and fields for analytical search to get the results they need to make a decision.
This blog post will serve as a plea on behalf of the average business user. When you choose an analytical tool to support your organization’s needs, choose a tool that is easy enough for each team member to use. If you want your business to improve productivity and data literacy, if you want to improve data democratization and you intend to provide self-service analytical tools for use by the average team member, choose a tool that Designed to make life as easy as possible. To each of those team members.
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Every employee is also a consumer in the real world, and they are used to handy tools. They know how to search for something on Google and get the results they need. The reason they can do this is simple: the equipment provided for this purpose is designed for human interaction. You ask a question, and you get an answer.
But analytical tools often fail to provide the same support.
While there are plenty of analytical tools out there, and some great augmented analytic tools that guide and suggest users, the concept of Natural Language Processing (NLP) cannot be encompassed in a way that supports similar Google-type search mechanisms. does.
And, when we take the NLP concept a step further and provide context, we give business users the ultimate, easy-to-use, analytical tools.
That tool will ensure that they adopt the technology and use it to make decisions every day, thus supporting faster ROI and lower TCO and improving productivity and fact-based decision making.
In addition, you will make your business users happy. No one wants to struggle to find the information they need to do their job or find out after making a decision that there was information that would have taken them in a different direction and improved the outcome. But business users are not IT professionals or data scientists. They know their jobs and may specialize in legal issues, financial investing, sales, marketing, or any number of other business activities, but they don’t get paid to focus on technology. So, if you want to empower them and hold them accountable for their decisions, give them the tools they need to easily access information.
Ask A Question, Get An Answer. Find the information you need and get informed about the issues.
Here are some examples of how context-driven NLP searches can inform your business users and help them make decisions:
Ask a question to compare costs: “What is the cost of materials to make a washing machine in Arizona vs. Arkansas?” Ask a question that reveals “most” or “least”, “high” or “low”: What was the highest temperature in Arizona in 2019 and when did it occur? Ask a question about a time without requiring specific dates: How many silk blouses were sold during the Christmas season in 2016 versus 2018? Ask about sales without specifying the name of the sales representative or a specific product: Who sold the most fruit in Phoenix, Arizona in the first quarter of 2018?
As you can see, this type of context-driven search allows the average business user to ask a question, using standard human language and following an idea or concept, to refer to this question as a system query or programming language. without language translation. So, your users can do their job, get the answers they need to improve the results, and get on with their day.
This concludes my plea on behalf of your business users.
If you want to improve outcomes, ensure fact-based decisions, increase data literacy, improve productivity and collaboration, and ensure great ROI and TCO (not to mention improving user adoption and user satisfaction) don’t), then check out Enhanced Analytics Solutions with Natural Language Processing (NLP) and context-driven search capability.