Data democratization can feel like just another business buzzword. But beyond the buzz, it represents an important concept: when your employees lack access to the data they need for decision-making, decisions will stall and your business will suffer.
Getting value from your data—and delivering that across your organization—is a persistent challenge. According to a Gartner® survey:
“Less than half of data and analytics leaders (44%) reported that their team is effective in providing value to their organization.”1
It’s not easy to get it right, and too many data solutions are full of empty promises that leave execs oversold, business users over promised, and IT burdened with yet another product that fails to deliver.
That’s why Appian invests in features and capabilities that add tangible value to even the most complex data ecosystems. And in our 23.4 release, we introduced a preview of Appian data fabric’s self-service analytics, a dedicated space for business users to explore enterprise data and build reports.
Many business intelligence solutions offer the ability to create custom reports. But the downside is that they're just BI solutions.
The Appian Platform delivers end-to-end process automation fueled by your enterprise data and AI. And self-service analytics is just one of many powerful capabilities that the platform delivers to extend the value of your data and processes further.
Because self-service analytics is powered by an underlying data fabric, it solves a lot of common challenges that businesses face when trying to democratize data access, like security concerns, data availability, and lack of real-time access. And because it leverages the Appian Platform’s low-code design capabilities, using it is incredibly easy—no prior Appian experience or development work necessary.
Ready to get started? Continue reading for a few ideas for how you can put this new capability to use. Or contact our team for a custom demo.
Self-service analytics allows business users to explore and analyze data in their Appian data fabric and browse a catalog of datasets secured by role-specific permissions and row-level security.
For example, if a retail bank wants to improve its customer retention and cross-selling effort, it can use self-service analytics to better understand customer behavior and identify opportunities for upselling and reducing customer churn.
With the necessary data already unified in their underlying Appian data fabric, the bank’s analytics and business users can now interact with available data based on their user permissions. They can do things like segment customer information and pinpoint opportunities for cross-selling. With reliable user permissions in place and strong security credentials, Appian ensures your data will only be accessed by the right people.
With self-service analytics, users can quickly design reports with grids and charts to aggregate, filter, sort, and format data as needed.
To build on the retail bank example in Use case #1, the bank’s analytics and business users can also create data visualizations to show things like the most common transactions, peak transaction times, and demographics of high-value customers.
From there, they can track the effectiveness of their initiatives and campaigns over time to optimize their strategies, gain a deeper understanding of their customers, and make data-driven decisions in real time.
Appian’s self-service analytics capability also includes Appian AI Copilot, a conversational AI assistant that can answer questions and share insights about your data.
And for extra security, bring your own key (BYOK) encryption allows you to keep your datasets private, so the questions you enter in the chat and the data you choose to include in your reports are only sent to your own dedicated instance of OpenAI GPT-4.
For example, users can ask AI Copilot questions about a report like:
What are two actions I can take based on this report?
What are areas for improvement?
What are the outliers in this report and how do I improve them?
[ Learn about Appian’s approach to AI. Download our Guide to Implementing Private AI. ]
1Gartner Press Release, Gartner Survey Reveals Less Than Half of Data and Analytics Teams Effectively Provide Value to the Organization, March 2023.
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