Why the Pandemic Accelerated the Decline of the Data Dashboard

摘要： Turns out, dashboards can't predict an uncertain future. Here's how they're shifting today, according to Gartner and other experts.

▲圖片標題(來源： InformationWeek)

One of the staples of business intelligence technology for years has been the data dashboard. Organizations could spin up a visual report that would be updated regularly, giving business users an up-to-date view of a variety of metrics deemed to be key performance indicators or KPIs.

It was an easy way to expose important data insights to business users who may not have the time or inclination to do their own data exploration. Serving up those insights in a handy way helped business users steer their organizations to achieve more by improving sales, operations, efficiency, or something else of importance to the business.

But in late 2020, Gartner predicted the decline of the dashboard as one of the top 10 data and analytics trends for 2021. That's not to say that getting an instant picture of where your business stands suddenly was no longer important. Rather, users actually wanted to go deeper into the data to learn more and gain deeper insights, according to Gartner VP Rita Sallam who described the trend at a Gartner conference.

Like so many other trends that were playing out more slowly -- digital transformation and remote work, to name a few -- pandemic has only hastened this prediction of the decline of the dashboard.

That's according to Cindi Howson, an expert on business intelligence software as the former president and founder of BI Scorecard, a former Gartner VP and analyst, and now Chief Data Strategy Officer at ThoughtSpot.

The impact of COVID on markets and consumer and business behavior meant that current trends could not be predicted by past data. The world was changing quickly. Why were dashboards falling out of favor?

"It was the pace of business change and the number of new questions that every organization had," Howson said. For instance, healthcare companies had questions about PPE equipment, and they may not have had those questions before. Retail companies were facing stock outs of toilet paper and needed to ask questions about the supply chain and customer demand.

"These were questions that weren't asked before, so they weren't on any dashboard," Howson told InformationWeek. "The process of creating a dashboard would take week or months, and you have to throw more bodies at it. Every customer I talk to talks about the dashboard backlog."

In its most recent Magic Quadrant report for Analytics and Business Intelligence released in February 2021, Gartner noted that data visualization capabilities, including the ability to create an interactive dashboard, is now a commodity feature for platform providers.

"Differentiation has shifted to how well platforms support augmented analytics," Gartner analysts Sallam, James Richardson, Kurt Schlegel, Austin Kronz, and Julian Sun wrote in the report. "Augmentation utilizes machine learning and artificial intelligence-assisted data preparation, insight generation and insight explanation to help business people and data analysts explore and analyze more effectively than they could manually. Rather than being a discrete capability, augmentation is now threaded through platforms as ML is applied across the data-to-decision workflow.

Howson noted that ThoughtSpot is one of the vendors that pioneered this capability. Gartner has placed ThoughtSpot at the top of the Visionaries quadrant in its Magic Quadrant report. Leaders in the report were Microsoft, Tableau, and Qlik. Other vendors under ThoughtSpot in the Visionaries quadrant were TIBCO Software, Oracle, Sisense, SAP, SAS, and Yellowfin. The Challengers quadrant vendors were Google (Looker), MicroStrategy, and Domo.

Howson also points to these capabilities in cloud players like Databricks, Snowflake, and Microsoft Azure.

These new capabilities take the conversation farther than a dashboard could, according to Howson.

"Now, rather than asking 'Can you create this report,' business people can say 'Look at this data and help me understand what it is telling me,'" she said. "That's much more of a business conversation and it is understanding the why and the what-to-do-about-it rather than just a data dump."

轉貼自： InformationWeek

若喜歡本文，請關注我們的臉書 Please Like our Facebook Page： 　　　Big Data In Finance