Leveraging Artificial Intelligence to augment Big Data Analysis

With gobs of data available just a click way, an organization’s overall success is directly proportional to the speed and accuracy at which this data can be processed into useful information, analyzed and acted upon.

 

Business intelligence tools do a good job at presenting this massive data, procured from various sources, in a pictorial or report format.  However, is this representation of data really understandable? Consider a sales manager who has to go through scores of sales reports and performance reviews of his team. Every month, he receives consolidated sales reports that look something like this one:-

 

 

Comprehending a report like the one above is a cumbersome and time consuming task. More so, there is a probability of missing out on useful insights due to limited human intellectual capabilities. Automated narratives that actually explain what the numbers in the report indicate in terms of performance and how relevant they are to the reader, is a great way out.

 

With automated narratives, the report would now look like this :-

 

 

This is certainly clearer, more detailed and explains all that one needs to know to aid decision-making.

 

Having a “virtual expert” over to generate such narratives is the smartest decision leading organizations are making today. The virtual expert is well-equipped with the analytical skills, domain knowledge and technical expertise to automate the process of data analysis and write lucid reports for you. It not only revolutionizes the way data is approached, but also seamlessly integrates into your existing architecture, while cutting down time and cost by a humungous amount. The output is generated in the form of comprehensive narratives in conversational language, within a matter of seconds. The virtual expert is based on Natural Language Generation, a subset of Artificial Intelligence (AI), concerned with generating language from input data and aimed at robotizing data analytics and report writing.

 

Business analysts spend hours trying to make sense out of pie-charts, graphs and tables and crunching numbers that never seem to stand still in the world of finance. Natural Language Generation (NLG) solutions automate this tedious, repetitive and resource-intensive task, giving out crisply written narratives coupled with statistical summary as the output. It is now easier to derive business insights and focus on decision making and strategic planning. The data isn’t subject to human bias, misinterpretation and error hence the output generated is highly accurate.

 

Intra-organization, such platforms can be configured to generate reports for everyone, whether it is an asset manager, a technical lead or an executive. The reports can be customized as per the level of detail and type of information needed. They go way beyond template-based report generation software and internally work on algorithms that emulate a human expert, albeit in seconds, and with much larger and complex data as input.

 

Having sent out quarterly customer portfolios, can you be certain that they understand where their investment is heading, or how good they are doing? In most cases, the answer is a big NO! The customer, in spite of being the most important entity here, doesn’t feel much involved. Automated narratives not only explain to the customers all that they need to know about their portfolio in simple language, but also do so in the tone and voice of your organization. This significantly improves customer engagement, making them resonate with your brand much better.

 

Such a virtual expert aids data analysis, empowers you to achieve optimum resource utilization, increase productivity by several notches, and generate more revenue.

 

Case in point, in a recent interview with the Wall Street Journal, the principal of Deloitte Consulting LLP had stated that deploying Natural Language Generation across the organization for business unit reporting led to a significant increase in organizational efficiency. Earlier, the process that required eight analysts, needed only one after the adoption of an NLG solution, allowing them to redeploy seven analysts to higher-value activities.

 

Also, with rapidly increasing data available in different formats across a variety of sources (termed as ‘Big Data’), it is crucial to do data interpretation on the fly and draw conclusions to exploit the current market trends and maximize profit. It is important to sift data real-time, reveal patterns that aren’t very obvious and generate accurate results. NLG platforms like PHRAZOR that not only provide automated narratives and interpretable reports, but also double up as big data analytics tools, serve the purpose. Thus, you can rest assured that insights aren’t buried, opportunities aren’t lost and you are making the most out of the data available, no matter how overwhelming it is, at the right time.

 

With Forbes declaring NLG as one of the hottest tech trends for the year 2017, it is here to stay and redefine the way we do business. It takes efficiency, innovation and progression to a new level, enabling leaders to stay ahead of the competition and be well equipped to tackle challenges in unprecedented ways.


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WRITTEN BY

Romil Shah

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.

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.

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