“By 2025, data stories will be the most widespread way of consuming analytics, and 75% of stories will be automatically generated using augmented analytics techniques”, per Gartner.
Data and analytics leaders need to stay ahead of the curve and begin leveraging ML/AI-based data storytelling .
Learn more about the newer approaches to data storytelling, their impact on decision maker engagement, and how to scale them organizationally.
“Self-service technology is only as useful as individuals’ capabilities to serve themselves. . However, many users lack the required analytic skills and data literacy to get the most from self-serve tools. In addition, they are often too busy dealing with business operations to spend time analyzing data,” per Gartner.
“This approach has the potential to analyze far more data than would be possible by an analyst population and to arrive at insights from data that are less colored by human attention and bias. Effectively, the data itself tells the story. But to do this, the software needs to have an understanding not just of analytic techniques, but what makes a good story from the users’ perspective,” per Gartner.
“Compare the automation level offered by emerging products like outlier.ai, Stories.bi (now owned by Workday), Narrative Science Lexio, datastories.com and Yellowfin Signals in data story creation with that offered by narrow NLG in A&BI,” per Gartner.
Read the full report by James Richardson, Senior Director Analyst, Business Analytics & Data Science at Gartner. June 2021.