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.
Everyone has heard the term ‘natural language processing or NLP. So, what is natural language processing, exactly, and how can it help your business? NLP allows a program or software to understand language as written/spoken by humans so that people can interact with a system without using long strings of code. You use natural language processing every day when you engage with your word processing software to perform spell check, when your smart phone auto-corrects your words, when you use voice to text messaging, when your email system applies a spam filter, when you are served keywords that relate to a search you did on a search engine and when you use ‘assistants’ like Siri or Alexa.
What is predictive analytics? Put simply, predictive analytics is a method used to forecast and predict the future results and needs of an organization using historical data and a comprehensive set of data from across and outside the enterprise.
Whether we know it or not, we use Natural Language Processing every day. It makes it easier for us to interact with computers and software and allows us to perform complex searches and tasks without the help of a programmer, developer or analyst.
The importance of data analysis cannot be overstated, but if the enterprise does not choose the right data analysis tool, it will not achieve its potential and it is likely to frustrate the business users who are now expected to participate in the analytical process.
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.
Data literacy is a very popular idea these days. As business users adopt and embrace data and advanced analytics, features like predictive analytics for business users make it easier for a user with average skills to leverage data to make decisions and share information and, in so doing, to become more literate about data analytics.
