How Can Natural Language Processing Change Business Intelligence?
Business today should be as adaptive and flexible as possible, with an ability to change quickly in response to market and environment changes. However, in order to make good business decisions – whether identifying new opportunities or building an effective business strategy – you need to be armed with data. So having quick access to information is critical for making rational business decisions.
Imagine how many piles of unstructured data McDonalds have to go through and analyze before they decide to add a new dish to its perfectly shaped menu? And the examples are endless.
Business Intelligence (BI): What It Is, What It Does
The digital age dictates its rules. What does it take for an organization to be successful? Primarily, its ability to use data and information promptly. The amount of information generated every second is enormous, no matter what business or industry one is in. Information capital could certainly become a huge competitive advantage. But the challenge is to make sense of that data and translate it into an actionable material. And here lies the power of business intelligence tools that help us navigate the data ocean.
BI is an umbrella term that refers to a variety of software applications used to analyze data and support a wide spectrum of business decisions, ranging from operational to strategic.
Why BI became so important?
First, because of the large volumes of data. Ten years ago you could analyze your corporate data just by using spreadsheets or excel (and some businesses, especially smaller ones still operate that way). Today we are talking about hundreds of terabytes (or even petabytes!) of data that require industrial-scale robust business intelligence solutions to get processed.
According to Gartner, the business intelligence market is forecast to grow $18.3 billion in 2017 (an increase of 7.3 percent from 2016) and $22.8 billion by the end of 2020. So business intelligence is a really hot market. And this boost is coming from the realization that business intelligence is no longer a luxury or a nice-to-have environment, but the ONLY way to go forward.
NLP-powered Business Intelligence
So what does Natural Language Processing (NLP) have to do with it all? And how is it destined to change future BI space?
The concept of Natural Language Processing is not at all difficult to comprehend. Natural language is everyday language humans use to communicate with each other. Imagine communicating with machines and computers in the same way you do with people? And NLP is the technology that makes this transformation possible (learn more about Natural Language Interfaces in our previous post).
In other words, you don’t need to learn programming languages to communicate with your computer, it will understand you and give you intelligible answers. So the main purpose of NLP is to help computers parse the ambiguity of human language. This is going to be the new era of human-computer relations!
There are a lot of current examples of voice commands and natural language understanding. Some of the apps you most probably have heard of, such as Watson (IBM), Siri (Apple) and Alexa (Amazon). Some NLP components are used in Google Translate and Google Searching.
Do you have guesses as to how NLP can change business intelligence? Let’s delve a little deeper into this.
Making data accessible to all
NLP goes hand in hand with business intelligence usage. The data based on which BI works can be made more accessible thanks to NLP. Interaction with databases and large data sets with the help of Natural Language Interfaces can change the way we interact with complex systems. In this way, it can help put more people in jobs that seem too technical. This drives many organizations to explore NLP as a way to connect non-technical users with the data they need to support critical decisions with.
Applying NLP to BI tools makes it possible for non-techie people to just jump in and start analyzing data themselves, rather than wait for IT analysts to run complex reports. The best way to call it is probably the ‘democratization’ of information access: everyone involved in the business process can have full access to information in order to be able to make informed decisions.
Getting better at “understanding” the query
The current state of NLP is more about translating natural speech into machine language. However, this focus is likely to shift towards making computers understand the query and deliver meaningful answers rather than raw search results. Soon it will be not just about being able to ask the question in natural language, but about receiving natural language answers too.
Apart from this, there are plenty other ways to advance business intelligence with the help of NLP, especially when it comes to text analysis.
For instance, structuring. It’s no surprise that a great deal of business-relevant informationoriginates in unstructured form, primarily text (which is understandable considering we are still humans).NLP helps reveal patterns in the scattered data making it more suitable for further analysis.
Another promising area of NLP application in BI is sentiment analysis - the use of natural language processing techniques to extract subjective information from a piece of text, also known as Opinion Mining. This method is already being widely used by brands to reflect customer sentiment, and determine if the social media buzz around their marketing campaigns is positive or negative.
And here’s one more - summarizing. A summarizer will generate a shortened version of the source text without changing the content and purpose of the original. Some media organizations are using NLP-basedplatforms to categorize, tag and summarize content and understandably so.
So these are to name but a few: the application of NLP-based methods in data analysis seems to be endless.
NLP Is The Future Of BI
With NLP, business intelligence will go a long way. The speed of data access, increased data quality will allow businesses to save time and budget on getting the ground ready for proper decision-making. Business meetings will take seconds to prepare for, acquisitions will happen in no time, candidates will be found immediately. Use your imagination to continue this chain of thought!
What the future holds is anyone’s guess. But the promises of NLP-powered BI usage are truly amazing. Natural Language APIs - like FriendlyData - can make data accessible to anyone and help us maximize the benefits of these upcoming technologies by turning them into fantastic business productivity.
In our next article that will come soon we will review and compare the TOP Natural Language Processing APIs - make sure not to miss it!