The digital wave has brought with itself a set of challenges and opportunities for businesses across industries. The explosion in the usage of the internet and smartphones has led to the accumulation of vast amounts of data which holds enormous opportunities for businesses. Big data when decoded and used in a relevant and timely manner has the potential to power industries and businesses into making informed decisions.
Whether it is tracking your company’s monthly spends or monitoring employee performance, there are mounds of data that would need decoding and cracking. Businesses often look for help to understand such data. A data analyst is typically skilled to analyze and convert the structured data into facts, figures, and tables. But you would still need his help to understand what those facts and figures mean for your business goals, and how you can use those insights to appeal to your end-user.
The key is to decode the data in an easy-to-understand manner and derive relevant information to articulate what your customers are looking for. With the attention span of customers becoming fickle day-by-day, it is more important than ever to harness their attention with the right information in the right way, at the right place. Deconstructing analytics to get actionable, useful, measurable, and reliable insights automatically, in real-time is the need of the hour.
Businesses often face challenges in combing and mining the right data and translating it into useful and actionable insights. Natural Language Generation (NLG) uses the power of language to automate this process and bridge the gap. In this article, we take you through how NLG can be effectively used to analyze big data.
Natural Language Generation is an advanced AI technology that transforms complex data sets into easy-to-understand narratives. It takes the gist of the data and creates a language that businesses and customers can understand and respond to. This is exactly the technology behind Phrazor- an augmented analytics tool that derives insights from data in words. Phrazor bridges the gap between cumbersome, cold data, and the potential benefits it can bring to businesses. It uses Natural Language Generation and Machine Learning to enable seamless interpretation and communication of insights with automated reporting.
Let us dig deeper into the various characteristics of Natural Language Generation that aid in deciphering big data and how Phrazor uses them to solve business challenges.
Language and Storytelling
Language is the key to generating a narrative from dynamic insights that everyone can understand and interpret easily. And, storytelling is effective in setting the context of transmitting the message and making an impact. Data storytelling has become critical to communicate insight to users in a manner that they understand. It can take on different storylines, plots and characters depending on the industry and function it is catering to, and produce a relevant combination of visuals and words.
For instance, in the sales function, the Employee Sales Performance Report tells the story of the overall performance of a sales employee in terms of the meetings conducted, deals closed, targets achieved, contribution to the overall revenue, etc. The plot thickens with comparing the performances of various sales employees, tracking specific sales KPIs, and analyzing the contribution of a specific employee to the overall growth of the company. The data stories vary with each industry, function and report and incorporate specific business domain context to make the report more relevant and insightful for the particular domain or user. Not just that, these data stories can be written in multiple regional and foreign languages, depending on the user's understanding.
Adding Context to Data Interpretation
Generating Valuable Insights
Data storytelling is the vehicle, but at the heart of reporting lies the effective use of Business Analytics to ensure that the insights generated are worth the users’ time and resource investment. The insights generated using Natural Language Generation must be valuable enough to provide new and significant inputs and answer questions such as- what is the data telling us, what is the implication of the analysis, and what does it mean to the end-users? They must be actionable and capable of making an impact in real-time.
So, what makes for a good, valuable insight? Here are certain requisites that make for good insights.
These insights give a clear picture and allow data to be understood and used beyond the basic interpretation. It provides deeper analyses and insights which can be used effectively by enterprises in bagging competitive advantage within the industry.
Phrazor is built by strategically linking AI, Data Science, and Business Analytics to generate useful and actionable insights in human language as per various functions and industry specifications. Its analytical engine is perpetually powered by built-in domain context and its wide range of use cases, which helps in deriving unique narratives.
NLG is fast becoming a workhorse for content generation in the business world. With the ability to harness the vast quantity of structured big data, the technology is evolving with innumerable applications and has the potential to change the face of every business from education to finance to media.
To see NLG in action, get in touch with us!
Romil Shah is an AI enthusiast with considerable experience across varied technology domains, primarily Natural Language Generation (NLG), and Blockchain technology. He is passionate about technological innovation and more importantly its real-world applications. His work within the field has brought about constructive conversations and explorations around AI and its extended use in businesses.