From artificial intelligence (AI) to machine learning (ML) to conversational chatbots, the tools we use to interact with and consume information are rapidly changing thanks to powerful new technologies that make understanding our data more accessible than ever. One particularly influential field is natural language technology (NLT) and its branches.

Being able to create and share insightful data-led stories to support your dashboards and reports is a critical capability in today’s modern workplace. You want your data to be accessible for more people, and ensure everyone gets value from your investments. Data storytelling tools bring valuable context to the ‘why’ behind the results, while inspiring your audience to care about and act on insights.

From ancient Greek myths of talking statues to the modern-day Alexa and Siri, the concept of machines capable of understanding and responding to human language has captivated us for centuries. In recent years, this concept has evolved into AI chatbots, highly sophisticated tools that can read our queries and perform tasks ranging from customer service to automated alerts.

In today’s fast-paced digital environment, delivering value quickly is critical to staying competitive and gaining buy-in from both stakeholders and customers. One of the key enablers of this rapid value delivery is embedded analytics, a business solution that allows you to integrate interactive data visualizations and business intelligence (BI) features directly into your existing applications.

Welcome to the latest entry in Yellowfin Japan’s ‘How to?’ blog series! This series of blogs aims to provide your team with another hands-on example of adding data visualization to your Yellowfin dashboards, using our array of chart and graph types. In the previous blog, we created a Combination Chart by aggregating on the basis of Year and Month.