We know that people learn in different ways - whether it’s visually or through language. People also like to create a narrative and share a story. The best way to do both of these things is in long-form documents, not dashboards. That’s why you’ll see a big focus on long-form stories in Yellowfin release 8.

As automation does more mechanical tasks, the role of the analytics department will change quickly. In the future, analysts will spend more time interpreting results and telling stories.

We’re in the early stages of a dramatic transition for the analytics industry. More and more of the jobs that were previously done by analysts are being automated. Technology is changing the way organizations receive information. People are being alerted to both good and bad news as it happens and this has profound behavioral consequences for organizations.

The BI industry has become synonymous with the dashboard, but dashboards aren’t great at most use cases, like helping users to find new insights or investigate data. It’s time for the industry to find new ways to deliver information to users.

There are three phases in the way the BI industry has approached automated analytics: 1) helping the user build a better dashboard, 2) assisted insights, 3) outlier and trend detection

Glen Rabie, CEO of Yellowfin, makes 5 predictions for BI and data analytics in 2019.

When most people think of Business Intelligence, they think of dashboards. But despite the fact that dashboards are the default approach to BI, there’s a range of business use cases today where dashboards are failing (miserably).

Many businesses think of BI as infrastructure but that’s the shortest step to failure. The reality is that BI should deliver long-term value to the organization. BI done well is not a one-off project focused on infrastructure.

When our finance team really started to integrate BI into their workflows, we saw substantial improvements in empowerment and efficiency.

All of the value that’s delivered from BI comes from the context, not the numbers. For decades 95% of the effort in BI has been spent in cleaning data, preparation, and visualization. But for people in the business, all of the value comes from the remaining 5% - when the numbers are connected to context in the business. It’s time for this ratio to flip.