Yellowfin explores the future of data storytelling

Augmented automated analytics will solve three key challenges to empower business users and subject experts to discover and develop compelling data stories more effectively.

Yellowfin has launched a white paper exploring ‘The Future of Data Storytelling: how narrative and automation will redefine the next decade of analytics’, offering valuable insight to organizations on the power and potential of future augmented and automated data storytelling solutions.

The white paper introduces the limitations of historic approaches that rely on static dashboards and data visualization to identify, communicate, and explore insights from complex business data. These rely on a level of data literacy that is not guaranteed among key business audiences and don’t offer the crucial context that drives understanding and action.

Data storytelling, in contrast, employs narrative techniques that help less data-literate audiences interpret what is in datasets and enable subject matter experts to add context not present in the data. This is driving the current demand for data storytelling capabilities as business analytics users specify new solutions.

Gartner reports that one in four business leaders view data storytelling as one of the most important capabilities of new solutions, and predicts that data stories will be the most widespread way of consuming data analytics by 2025.

The intersection of data storytelling and augmented analytics

Yellowfin’s white paper examines how augmented analytics in modern BI tools are automating the data analysis part of the narrative process, making analysis more comprehensive and efficient. It also explores how technologies such as AI, natural language query and machine learning can help users to better understand what their data means.

However, as Yellowfin VP EMEA Geoff Sheppard explains, data storytelling remains largely human-driven and manual: “Humans will always play a role in data storytelling, as they have an unmatched ability to add context and emotional intelligence that is not present in the data. But by automating the parts of the data storytelling process best suited to machine support, we help users become more efficient and make data analytics tools useful to a broader business user base.”

Yellowfin identifies three emerging challenges that automated and augmented data storytelling can potentially solve:

•Human bias: data storytelling relies on humans to spot anomalies and find them important enough to explore further, but levels of interest and diligence vary from person to person. By adopting AI and machine learning analysis of datasets and extending this with a storytelling module, helpful data-led narratives could be generated that might have been missed, overlooked or undervalued when created by people.

•Low data literacy: levels of data literacy vary, making self-service analytics solutions too complex for less able users. By automating common self-service BI processes, the need for high data literacy is eliminated, and insights are presented in a digestible way for a broader user base.

•Scaling data storytelling across the business: as a human-led activity, scaling it across the business may be unrealistic. However, by extending automated business monitoring and analytics past alerting capabilities, data stories can be generated at scale.


AI’s capability to automatically generate augmented data stories with the level of emotion, relevance, context and narrative expertise as humans can provide is not yet a reality. However, as Geoff Sheppard explains Yellowfin 9.6, launched earlier this year, already employs analytics techniques that enhance the user experience and start to solve those three challenges:


“Our Assisted Insights automates part of the interpretation of data for the user to create stories from, reducing the data literacy needed to gain value from analytics. Our ABM product Signals delivers automated continuous monitoring that detects patterns or outliers in data, generating headline alerts to help users become aware of important discoveries.


“In combination, Assisted Insights and Signals enable the rapid discovery and analysis of large amounts of complex data, communicating insights in a way not influenced by human bias. These automatically generated explanations of data, and alerts of new trends or notable changes, can effectively act as an impetus for the data storytelling process. Together with Stories and Present, Yellowfin’s world-first dedicated data storytelling modules, users can find problems and opportunities in data faster, and create stories from those automated results using the power of data, words and rich media.”


Yellowfin unifies all these powerful, automated techniques into a single pane of analysis, with AI- generated interpretation of insights, automated alerts, and data storytelling all feeding into a dashboard that can become part of every user’s BI workflow.


“Humans will always be the drivers of data storytelling,” concludes Geoff Sheppard. “Algorithms just cannot create the rich, contextual narratives that come naturally to us. What they can do, however, is point the way, guiding and alerting us to points of interest that might be overlooked and prompting us to build more effective, engaging and valuable data stories.”


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