This post is sponsored by TIBCO. Thank you for supporting the organizations I trust.
In the previous post of this series, we questioned whether approaches to analytics have changed to account for the post-pandemic world. In this post, we’ll specifically look at the current typical approach to dashboards, and how this could be enhanced with converged analytics.
What most dashboards do now
Most dashboards today are developed by business intelligence (BI) professionals to provide trends and relationships in the data to business partners. While this data can come from a variety of sources such as data warehouses, data lakes and flat files alike, it’s nearly always historical.
These dashboards can answer what happened, and why it happened. They are often static, rearview analysis built on predefined queries, not responsive enough for more exploratory applications. But they become more limited when the user wants to explore what might happen next, and what to do about it..
What dashboards will do next
For those types of insights, dashboards must be able to more easily implement machine learning (ML) and artificial intelligence (AI) models, which have been developed mainly by data scientists, with little BI collaboration.
According to a study by Seagate and International Data Corporation (IDC), 30% of all data will be real-time by 2025. To provide a 360-view of the business, dashboards must also include streaming data.
Welcome to a converged dashboard
Imagine a dashboard that can use data to make decisions the way popular phone navigation apps, like Google Maps or Waze, use and serve up data. It could automatically give you the information you need and the actions you should take through a seamless convergence of predictive and real-time analytics, along with historical trends.
Through converged analytics, this is what future dashboards are capable of. Consider the following use cases:
- Perform descriptive analytics and visualization on streaming data
- Clean and transform data sources aided by artificial intelligence
- Deploy machine learning models to add predictive elements to historical trends
- Create alerts, open service tickets and send other triggers in real time directly from the dashboard
As I write in the Modern Analytics Platforms ebook:
“With converged analytics, individuals no longer need to wait for data science teams to provide ad hoc deeper insights. They have all the data-driven insights at their fingertips, assisted by AI to quickly explore and make decisions.”
Preparing for the shift
To learn more about how converged analytics can close the gap between insight and action with dashboards, get your FREE copy of the Modern Analytics Platforms ebook, courtesy of TIBCO.
As mentioned previously, converged analytics changes the way data professionals collaborate. Our final post of this series will examine the impact of converged analytics on the data analyst career and the so-called “citizen data scientist.”
Leave a Reply