However, it has high hopes. It can shine on the super-bright features of query and insights already built into the ambiance of the analytics experience. With it, the whole concept of Q&A gets a new meaning. Users can ask natural language questions about their data. The Copilot refines queries, suggests new phrasings, and makes recommendations to increase result accuracy. For instance, if you ask, 'What are the sales trends for 2023?', Copilot suggests additional filters or visual formats to represent data better.
It's almost like Copilot would be that co-assistant: what follows under Insights, finding all the patterns or anomalies would further aid users in digging deeper into those effects. It could suggest valid follow-up questions, create visuals on the mentioned insights, or provide some form of contextual information around the patterns detected. For example, if Insights reports that a sudden spike in sales occurred, Copilot might recommend looking at other metrics, like the marketing campaign's data, to find correlations.
The marriage of such elements is meant to develop users so that they can dive deep into their findings without much effort so that even nontechnical persons can reach their goals of getting actionable outcomes from such very complex systems.
