We all understand the value and innovation inherent in natural language processing (NLP). Think about the ease of searching for the answer to a question on Google. Users with average skills can ask a question and get an answer, a list of search results that address their interests and support and assistance to take the next step.
Whether you know it or not, you are familiar with Natural Language Processing. Applications of NLP include search techniques used in Google and other popular tools. The use of natural language processing in self-serve advanced analytics solutions can mean the difference between a simple, yet sophisticated, business user tool and a tool that is only suitable for a data scientist or professional analyst.
Whether you are a consumer or a business user, today’s technology users are savvy and they are used to having easy-to-use tools and features that make them more productive and allow them to quickly complete tasks. The same holds true for users of advanced analytics users. These users are also consumers when they are off the job and they are used to simple search technology like Google and other search methodologies that allow them to think, search and get results in a way that is fitting for normal speech and language.
Business markets and competition are moving much more quickly these days and predicting, planning and forecasting is more important than ever. It is also important to ensure that every team member is a real asset to the organization and can contribute their knowledge and skill with full Insight into the effects and outcome of activities and processes and the ability to correct the course and make recommendations using clear, concise information. Advanced analytics is the logical tool to help a business optimize its investments and achieve its goals.
Imagine a world where data science and predictive analytics tools are created for business users! That world exists today with the evolution of sophisticated, yet easy-to-use tools that include predictive analytics for business users, visual analytics software and tools, and self-serve data preparation.
As the need for advanced analytics increases in organizations, enterprises large and small struggle to find and sustain the professional resources they need to meet their requirements for data, analysis and strategic direction.
Natural Language Processing (NLP) takes the shackles off business users and provides advanced search analytics that is as easy as using a search engine. When advanced analytics incorporates natural language processing, business users can formulate questions and receive answers in a way that mirrors human language and writing. They do not need code or specific formats. They can just enter a question and receive an answer.
Many organizations have grown comfortable with their business intelligence solution, and find it difficult to justify the need for advanced analytics. The advantages of advanced analytics are numerous and those advantages are based on the ability to further improve the business, increase user adoption (and therefore user empowerment and accountability) and, best of all, improve the bottom line and the accuracy of predictions and forecasts that will dictate the success of the business in the future.
The impact of natural language processing (NLP) on the productivity and decision quality within an organization cannot be overstated. As simplified search analytics expands into all corners of the enterprise, the business can expect business users to embrace advanced analytics and, in so doing, to become more of an asset to the organization.
Everyone knows how to ask a question using the Google search interface. It is easy because it allows the user to phrase the question using normal, human language. Imagine how few users Google would have if they required the user to know and use complex search queries to find a restaurant or locate a movie review!
