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How Does Augmented Analytics Power Decision Intelligence?

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    In analytics and business intelligence, interactive reports, rich visualizations, and built-in capabilities are no longer enough. At the very least, they aren't enough to change a business so that it can use more advanced Business Intelligence tools. Many people will keep using their favorite spreadsheet tool because they are used to it. But data teams are being pressured to make BI easier to set up, manage, and use. This is why marketing buzzwords like "self-service," "data literacy," “No-Code Business Intelligence platform,” and "data storytelling" are so popular when trying to get people to use modern BI platforms. 

     

    Augmented analytics and Decision Intelligence (DI) are taking the analytics world by storm because they make analytics and Business Intelligence (BI) easier for both experts and people who aren't experts. Research from Enterprise Strategy Group (ESG) showed that augmented analytics is getting the newest net investment of all the features available in BI platforms. Its use is expected to grow by 88% over the next year.

    Why is Augmented Analytics helpful in Decision Intelligence?

     

    In the best analytics environments, AI is used to help with modeling, discovery, visualization, and storytelling. Augmented analytics that is easy for people to make sense of the source of the data and the people who use it. 

     

    In Gartner's report on the 2022 Critical Capabilities, the Decision Intelligence Platform from Pyramid Analytics was named the leader in augmented analytics. Here is a closer look at the AI-driven processes in the report that define augmented analytics and make this flow possible: 

    Businesses ask their analytics tools questions in everyday language, either by typing or speaking. For example, a manager can use an NLQ Chat Bot to interact with and look into data from a dashboard without knowing the data's structures, hierarchies, and measures underneath. No-code Business Intelligence is also slowly gaining popularity with the convenience it offers. 

     

    Automated Insights: Based on the query, the platform finds the most critical attributes in a dataset and then gives people actionable insights they can use or change as they wish. For example, a business manager can access at-a-glance dashboard reports, which can keep help streamline business operations. 

     

    Natural language generation: According to Gartner, the platform automatically creates "linguistically detailed descriptions of insights found in data." "In the context of analytics, as the user interacts with data, the story changes dynamically to explain key findings" or what data visualizations are trying to say. Imagine that a front-line worker could explain a complex data set by pointing and clicking and that the textual commentary and visualizations would be made automatically. 

     

    Data storytelling: The platform lets users combine interactive data visualization with storytelling techniques so that they can be packaged, reused, and shared with other decision-makers. For example, instead of going through a huge table of contact and opportunity records one by one, a marketing analyst can use Grow’s dashboard to find out about the most likely accounts to convert. 

     

    No matter the use case, augmented analytics can help people make better decisions and even help their colleagues make better decisions when they share their findings. This puts into perspective one of the most exciting benefits of decision intelligence with augmented analytics: the ability to drive personalization and, by extension, the adoption of data-driven decision-making across the whole organization.

    Conclusion

    Leading the future of decision intelligence. 

     

    We are moving into a world where anyone can use analytics to meet their needs by making their own discoveries in a governed self-service environment that is made for their role. People in all parts of an organization need to make decisions, respond, take advantage of opportunities, and make corrections faster because of the current economy. 

     

     

    There will be a big change in how companies scale to meet the analytical needs of their non-technical employees in the next ten years. Organizations that stay in business and do well will make many more decisions based on data because they use decision intelligence with augmented analytics to make experiences more personalized and interactive.

     

    Grow is one such provider of no-code Business Intelligence software where analytics-driven decision-making can help us succeed. 

     

    No-code Business Intelligence solution is a rising field where companies can easily prepare intuitive dashboards using drag-and-drop features. To learn more about Grow dashboards, read Grow Reviews Cost & Features GetApp. 

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