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TDWI Upside - Where Data Means Business

Natural Language Generation: 3 Reasons It's the Next Wave of BI

Today, it's everyone's responsibility to communicate, understand, and act upon data. Natural language generation helps provide understanding for those who aren't data experts.

As the field of business intelligence (BI) rapidly evolves, so does the technology supporting and advancing the industry. Natural language processing (NLP), a subset of artificial intelligence that allows software to understand human language by transforming words into structured data has established a place for itself in business intelligence and is a commonly used term throughout the industry. More recently introduced to the field of BI and analytics is natural language generation (NLG). Also a subset of artificial intelligence, NLG transforms data into clear, natural language to provide a complete contextual understanding by delivering written analyses that supplement data-driven charts, visualizations, and dashboards within BI platforms.

For Further Reading:

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Natural language generation takes the ambiguity out of data visualizations by communicating insights in the most universally understood way -- the written word. NLG is currently used in over 50 industries, including healthcare, government, financial services, and consumer goods. Although each specific use case may be completely different, the benefits of NLG remain the same: scaled analyst expertise and increased data literacy leading to better, faster decisions.

Scaling the Expertise of Your Best Analysts

With an increased number of people from various technical backgrounds working with BI, insight discovery and communication can be a challenge even with powerful tools such as data visualization platforms. As a result, end users typically need analysts to provide additional context for data sets. Critical analytics and data science resources are frequently overutilized writing weekly reports or responding to questions, limiting their timely availability and creating an organizational burden.

Compounding the problem is that data experts and analysts are in short supply. Even if they have enough time to construct reports for multiple teams across an organization, it's more advantageous for organizations to use analysts' expertise on higher-value tasks, such as expanding data analysis throughout the enterprise, projecting future business using predictive analytics, surfacing fresh and pertinent insights, or creating dashboards that more accurately measure the health of an organization.

By enabling analysts' teams to embed their expertise directly within a dashboard using NLG, critical insights can be delivered to, shared with, and understood by more people within an organization in a fraction of the time. Because users will have easily readable insights when viewing their dashboards, the benefits of analytics platforms and tools across an organization rise. Leveraging NLG technology to drive automation and innovate solutions provides each consumer with custom analysis. Converting endless numbers into meaningful insights gives users the ability to uncover trends and empowers them to confidently take data-driven next steps.

Increasing Data Literacy

Literacy is the ability to derive information from the written word. Data literacy is the ability to derive meaningful information from data. Companies are inundated with facts and figures, but these are without value unless viewers can understand what they mean. Data literacy is a critical skill; 80 percent of organizations will "initiate deliberate competency development in the field of data literacy" by 2020, according to Gartner. These initiatives are driven by data teams striving to increase their company's ability to "speak data." The gap in organizational data literacy can be a roadblock that, if not bridged, will hinder a company from reaping the full reward from its BI and data investments.

Analytics used to be a highly specialized field only found in small subsets of teams within large organizations. Today, almost every role in the modern business landscape has the opportunity to interact with and benefit from data analysis. From C-level executives and non-data experts to seasoned data scientists, NLG breaks down the barrier of intimidation surrounding big data for those who aren't fully immersed in the world of reading numbers. NLG removes the stigma that data can only be understood by a select few within a company and empowers organizations to be data literate from the ground up by providing a way of understanding.

As a result, NLG reduces misinterpretation of results, increasing profitability by decreasing time spent debating what the numbers mean. The conversations shift from "I think" to "I know" because teams are equipped with an accurate, single source of truth and can "speak data."

Better, Faster Decisions

Having the power to understand and act on data is transformational for organizational development. Individuals in your organization can unlock the power and knowledge hidden within their data, enabling them to make better decisions faster. Instead of spending time parsing charts and visualizations, hunting for key insights and unsuccessfully trying to understand what they mean (or getting a glimpse of the whole picture but missing less obvious insights), users are able to instantaneously know what the issues are and what to do about them.

It's like a puzzle; you can align the border pieces and have a general outline of what the puzzle will look like using the picture on the box, but there are still hundreds of missing pieces. Those missing pieces hold the entire story of the puzzle. Natural language generation is the key piece to reading the entire story of your data, to making sure insights aren't missed among the noise of numbers. It inserts all the pieces to finish the puzzle and creates a foundation for you to quickly and confidently make accurate, error-free decisions knowing you're seeing all key insights.

A Final Word

In our data-driven world, it's now everyone's responsibility to communicate, understand, and act upon data -- the role is no longer solely reserved for experts. Natural language generation helps bridge the gap between analyst and organization, providing contextual understanding through storytelling for the immense amount of data to steer companies and individuals towards superior decisions that put them one step ahead.

About the Author

Marc Zionts is the CEO of Automated Insights where he's responsible for the strategic direction and execution of the company to accomplish short-term goals while constantly working towards long-term objectives. You can reach the author via email, on Twitter, or LinkedIn.


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