A unified experience that brings together data storytelling and data visualization highlights the latest Yellowfin analytics platform update.
Data storytelling is the automatically generated interpretation of data in a narrative form. Its intent is to make data easy for business users to understand without requiring a background in data analysis.
And because of its easy-to-understand format, some analytics industry observers think data storytelling has the potential to finally make data analysis and interpretation accessible to nearly everyone in an organization, rather than just an estimated 20% to 40% who have data literacy skills.
Yellowfin, founded in 2003 and based in Melbourne, Australia, first introduced Stories, its data storytelling tool, in 2018.
Stories to dashboards
On July 1, the vendor unveiled version 9.6 of its analytics platform, and with the release of the update, Stories can now be incorporated directly onto dashboards. Previously, Stories and dashboards were separate, and Yellowfin users had to toggle between the two environments to see the automatically generated narrative about the data visible in the dashboard.
The result is greater context, according to Glen Rabie, Yellowfin's CEO.
"Ultimately, as part of an analytics solution, our customers do want to deploy dashboards to their end users," he said. "By adding stories that are contextual to a specific dashboard -- for example, sales reports on a sales dashboard -- you can elevate the value of that dashboard and make it a single place for users to go to understand what happened and why."
The development of that single view for understanding what happened and why, meanwhile, is both practical and inventive, according to Donald Farmer, founder and principal of TreeHive Strategy.
In addition, it demonstrates Yellowfin's focus on data storytelling as a key aspect of its platform rather than merely an add-on capability.
"While other companies experiment with storytelling and augmented features, Yellowfin has been really working well with customers to develop practical scenarios," Farmer said. "It's all quite pragmatic, but still innovative. In particular, integrating stories into the regular workflow of a user shows how serious Yellowfin is about making these features part of the daily practice of a business user."
Glen RabieCEO, Yellowfin
According to Farmer, the only analytics vendor whose data storytelling capabilities rival or exceed those of Yellowfin is Narrative Science, whose sole focus is data storytelling.
"In short, Yellowfin continues to innovate closely with its customers, and it shows," he said.
Customers, meanwhile, were a primary driver for developing a more unified experience, according to Rabie.
Yellowfin previously enabled customers to embed Signals, the vendor's automated alert capability, onto analytics dashboards. Based on the response it received to that innovation, it decided to enable customers to embed Stories in dashboards as well.
More new features
In addition to a more unified experience, Yellowfin 9.6 includes 23 other capabilities. Among them are:
- Story Templates, a tool that enables customers to use existing data stories as templates, giving them the ability to customize narratives while saving them time by providing repeatability;
- Story Filters, a capability that enables story authors to set and save filters directly within stories that contain embedded reports and charts;
- new visualizations on Yellowfin's Chart Builder that help data analysts do more chart customization with new options for axis values and labels, category spacing and category sorting; and
- enhanced data governance capabilities with SAML (Security Assertion Markup Language) Authentication that supports native identity provider configuration to enable IT and DevOps teams to set and manage authentication parameters directly within the Yellowfin platform.
While the primary focus of Yellowfin 9.6 is data storytelling, the focus of the next Yellowfin platform update -- expected at the end of the year -- will be self-service analytics, according to Rabie.
The concept of self-service analytics is nothing new, but enabling true self-service remains a struggle given the varied data literacy levels of business users. Autonomy, meanwhile, is now as necessary as ever because so many employees are working remotely due to the COVID-19 pandemic and the likelihood that many will want to continue to do so even as offices reopen.
"It's something that we have been working on for quite a while that [we hope] will reshape how business users can achieve true self-service," Rabie said of the next release.