“Visualizations are a powerful and consumable way to communicate patterns in data versus tables or lists. However, they do not always highlight statistically significant findings. They require user interpretation to determine whether findings are relevant, significant, and actionable. Moreover, finding insights from advanced analytics — a holy grail for most companies — requires chronically scarce specialized data science skills.”The solution? According to Gartner, it is an approach to data analysis called smart data discovery. This provides non-technical users the ability to discover insights in advanced analytics data without requiring any knowledge of data modeling or algorithms. As we’ve talked about before, data needs to be accessible by all employees, not just the data-savvy. However, gathering this information isn’t enough, you need to use the data quickly and effectively. The best way to do this is by using Natural Language Generation (NLG) software, which can generate text that is able to explain the insights hidden in the data.
So why is it smart data discovery needs NLG?
- Identify and Implement Data Insights in Real-Time: Smart data discovery helps to identify valuable insights, but there often can be a delay from identifying those insights then developing and implementing a solution or response. With NLG, a written synopsis is provided, in real-time, taking the guesswork out of identifying and implementing the next steps.
- Provide an Interactive Customer Experience: If you’re implementing insights and solutions in real-time using NLG and smart data discovery, clients can receive personalized feedback quicker. Not only does this help decrease workflow times, but customers feel like they’re receiving one-on-one treatment, boosting customer experience.