A report from the International Data Corporation (IDC) revealed that global data will likely increase ten times to 163 zettabytes by 2025, with enterprises creating 60% of the world’s data. Given this mountain of data, organizations can unlock a new world of business opportunities by transforming these data sets into insightful narratives through natural language generation (NLG).
But what exactly is natural language generation (NLG) and how can companies leverage this to stay ahead of the curve and gain a competitive advantage? This is where Automated Insights can help. As the creator of the world’s first self-service natural language generation engine, Automated Insights aims to empower businesses by transforming data into clear, human-sounding, and insightful narratives.
SourceForge recently spoke with Laura Pressman, the Marketing Manager at Automated Insights, to discuss the advantages of using natural language generation and business intelligence and analytics platforms. Pressman also shared some insights on Wordsmith and how this powerful Natural Language Generation (NLG) Platform can help fast-track data literacy efforts and enable businesses to fully utilize and make sense of their data for faster, better, and more accurate decisions.
Q: Please share with us a brief overview of Automated Insights. Who are some of the clients you are currently supporting?
A: Automated Insights is the creator of Wordsmith, the world’s first public natural language generation (NLG) platform.
Laura Pressman, Marketing Manager at Automated Insights
Established in 2007, Automated Insights supports a variety of industries, including data analytics and business intelligence, financial services, sports, media, and more. Some of our key clients include the Associated Press, Yahoo, NVIDIA, Allstate, the Orlando Magic, and many others.
Q: How has Business Intelligence (BI) and Analytics reshaped today’s business landscape? And how does it impact business performance management?
A: Every modern business collects data in a variety of areas and departments, but aggregating this information for better market understanding and process optimization has been made easier and more accessible by business intelligence and analytics technology. Today, departments that previously operated on status quo or historical frameworks are now more empowered to question those processes and have stronger decision-making capabilities. They also need to take action to address trends in their data in real-time.
Q: What are some of the challenges and/or roadblocks that organizations face when implementing a business intelligence and analytics platform?
A: A major challenge organizations face when implementing BI and analytics platforms is getting organization-wide adoption of the technology.
Role-based Natural Language Generation
Often, companies deploy tools within specific departments but fail to properly train or showcase how it fits into organizational-wide daily operations. Also, dashboards with a ton of different metrics and visualizations can appear overwhelming or confusing to non-data experts. Providing a way for everyone, regardless of their level of data expertise, to understand what these tools are showing and quickly pull value from them is essential for implementing them widely in an organization.
Q: To make effective tactical and strategic decisions, organizations need to leverage a powerful BI and data analytics platform that can help turn data into unique, actionable insights in order to drive decision-making processes and create competitive advantage. In your opinion, what constitutes a reliable BI and analytics solutions?
A: Reliable BI and analytics solutions are platforms that empower the end user with all the tools they need to handle and transform data, derive important insights, and then give customers the ability to share and communicate this knowledge across their entire organization in a variety of formats. For example, a reliable BI and analytics solution should empower an analyst to take multiple sources of data, create dashboards with visualizations and narrative analysis, and share this information easily with variety of roles—from hundreds of branch managers to a team of executives, all of whom can interact with the information to better position their business in the market.
Q: When discussing business intelligence and analytics, we often hear the term Natural Language Generation (NLG). What exactly does it mean and how does this solution work?
A: Natural language generation (NLG) is the software process for transforming data into a human-sounding narrative. NLG solutions are made of three main components: the data behind the narrative, the conditional logic and software that makes sense of that data, and the resulting content that is generated. The main requirement for natural language generation is ownership or access to structured data, as this has a defined format where specific values are categorized into distinct sets. The output is powered by the narrative design, which is constructed by the end user and consists of conditional logic rules that trigger different outputs based on the data input behind the content. Within BI and analytics tools, NLG through Wordsmith means that as a user explores the data behind their entire dashboard, narrative analysis adjusts in real-time to reflect what the user is viewing. Pairing Wordsmith-powered written analytics with visualizations creates a more complete understanding of an organization’s data, empowering companies to make faster, more accurate decisions.
Q: In what ways can Natural Language Generation (NLG) help fast-track data literacy efforts?
A: One major way that NLG helps fast-track data literacy efforts is that it creates analytics presented in natural language that are unambiguous. Even data novices can read and easily understand the language that NLG produces to automatically explain a dashboard. In turn, it helps overcome lack of BI or analytics platform adoption within an organization because non-data experts are able to log in and engage with a dashboard and understand what they’re seeing immediately. NLG can also help automate the explanation of why certain trends are occurring in the data and utilize an analyst’s knowledge to generate prescriptive action items in response.
Q: Tell us a bit more about Wordsmith, the world’s first self-service natural language generation engine. What are its key features and capabilities?
A:
WordSmith, the World’s First Self-Service Natural Language Generation Engine
Wordsmith is the self-service natural language generation solution that enables complete narrative customization, real-time content updates, and a powerful API for flexible report publishing. With integrations with the top business intelligence and analytics platforms, companies are able to understand and act upon their data in a quicker, more accurate manner by delivering natural language insights and analysis in a written format.
Q: What can customers expect from Automated Insights in the future? Are there any new developments and/or product offerings that customers should look forward to?
A: We’re working closely with business intelligence and analytics providers to further integrate with the tools many organizations already use. For example, the ability to add Wordsmith from Automated Insights and receive truly insightful, prescriptive narrative directly in a dashboard at the click of a button is an area we’re focused on. Our partner network has been rapidly expanding as well to accommodate the growing market interest in NLG for BI as well.
About Automated Insights
Headquartered in Durham, North Carolina, Automated Insights specializes in natural language generation, business intelligence, software development, content creation, big data, and more. Using clear, natural language, Automated Insights aims to help users make sense of the world’s data and support data-driven companies to achieve content scale, efficiency, and personalization. Through Wordsmith, the world’s first publicly available natural language generation (NLG) platform, Automated Insights enables companies to transform raw data into narratives, such as summaries, headlines, articles, interactive application content, and embedded narrative that pairs with visualizations such as tables, graphs, and charts.