With the advent of technology, there have been various transformations that have impacted the lives of mortals. To this advancement, Natural Language Processing (NLP) is one such addition that has been designed to enable communication between machines and humans.
This technology itself is a wonder, otherwise, who would have thought that one day we will be talking to our mobile phones like a friend and asking it to play our favorite music.
Since, the interaction between machines and humans cannot happen using a regular language, that is when NLP comes into play. It has been developed with the convergence of Computer Science, Linguistics and Machine Learning.
NLP allows computer software to understand and respond in human language, though, it is first processed in computer language itself and then converted further for communication to take place.
This facilitation, if integrated with Business Intelligence (BI) which is a technology oriented process for analyzing of data and proposing suitable actions for corporates can prove to be a complete game changer when taking business decisions.
Let’s check out the impact of both these technologies when implemented together.
BI to become more insightful with NLP
At present, NLP turns natural language into machine language. With the passage of time, the evolution of technology will enable computers to understand the question better and respond to it accordingly. It will not produce search results as it used to do. For instance, the data chatbox will pick up the question – How revenue generation have changed over past three quarters? and reply to it with data pages to be analyzed.
However, once it gets acquainted to the semantic relations and inferences of the question asked, it will automatically filter to provide the relevant answer, instead of coming up with the data only.
Democratization of data
With the usage of NLP, the hindrance into BI and big data access, in general, will be removed. There are many organisations in BI that are accepting this trend and making data more and more user-friendly and accessible.
Supposedly, by turning BI into a conversation with a chatbot, the information will be accessed easily on the go as GUI requirement will be removed.
The queries will be made by text or voice commands on smartphones, while the processing will be done in the cloud.
The data chatbot will also answer questions about the sentiment of the customer in the present hour and what they will feel about the brand in the upcoming days.
Harnessing of unstructured data
By making the unstructured data understandable to a machine, the NLP functions to expand the scope of what answer will rest upon.
The initial attempts of sentiment analysis already go beyond detecting when. To consider, if a tweet is about your organisation, so to analyze the text surrounding and determining the tweet is positive, negative or neutral.
