Technology research and consulting firm, Gartner, predicts that, ‘By 2023, data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs.’
This article should serve as a plea on behalf of the average business user!
Business users are business professionals who have expertise in an industry or market arena or perform a function to support the ongoing operation of the business – professionals who may be front line workers on a production line, finance professionals, sales representatives, non-profit 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 a SQL query, or to filter out the columns and fields for an analytical search in order to get the results they need to make a decision.
The What and Why of NLP Search Analytics and How it Can Help Your Business!
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. 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.
Small and medium sized businesses (SMEs) are often challenged to satisfy all the roles and responsibilities in the organization and most team members wear more than one hat. That feeling of being overstretched is typical of growing businesses and, in an increasingly competitive market with businesses fighting for skilled resources, it is difficult to meet budget and scheduling goals and get it all done.
Natural Language Processing (NLP) may not be a term that everyone is familiar with but all consumers and business users are certainly aware of its power. You use natural language processing every day when you perform a search in Google using questions written in the same way one would speak or write to another person. Whether you know it or not, you are using NLP to process, interpret and return results that meet your criteria.
What is Natural Language Processing and Why Do I Need it in My Advanced Analytics Solution?
What is Natural Language Processing (NLP)?
Natural Language Processing utilizes artificial intelligence to translate computer code and language into real world, human language. While the goal is to simplify human interaction with computers, NLP is a complex mix of computational linguistics and computer science. When a business is considering an augmented analytics solution that leverages natural language processing, it need not concern itself with the complicated underpinning of code and design, but should rather consider what NLP can do for its users and for its business results.
The focus of this article is on Data Democratization within the business enterprise, but the concepts and approaches involved in implementing this type of initiative are worth considering for any kind of major change within an organization.
Augmented Analytics: Insight Comes from Perspective!
Perspective is everything. You can stare at numbers and columns all day and never see the one nugget of information that will give you insight and help you solve a problem or find that one opportunity to drive the business to the next level. When you and your business users can leverage augmented analytics tools, without worrying about complex algorithms or writing code or designing reports, you can find those elusive nuggets of information and use them to improve your business results.
Make the Most of Your Team Member Skills with Augmented Analytics!
Every business owner and manager understands the problem of limited resources. Today, you have fewer team members and you must do more to compete in the market. To enhance productivity and collaboration and ensure that every team member is making better decisions, it is wise to implement augmented analytics within your organization.
Users Might Think Augmented Analytics is Too Difficult. That’s Not True!
If you are a business manager who wants to enable a Citizen Data Scientist environment, but you find yourself up against resistance, it is often because your business users believe that advanced analytics is just too hard for them to learn and that the use of these types of techniques and systems will slow them down and confuse their otherwise familiar processes.