A new era of Business Intelligence requires new ways of thinking about and delivering insights. Gone is the just-in-time churn of endless dashboards! Read on to see what takes its place.
Build the strongest roots, allow the most flexibility towards the ends of the branches to grow towards the most nutrient-rich light (insights) as possible. Find the best trunk (metrics) that allows for the most types of branches to grow. Make sure that the ends of the branches have a way to transfer those increasingly nutritious insights back to the roots. Easy enough?
Can you think of an example of discovering a new insight/metric during exploration/discovery and then what the current as-is state would be to export out or push that insight back down to ML/AI apps, or even a new dashboard?
Yeah, imagine I'm using Tableau to do what they used to call 'visual data discovery' and I do a market segmentation that looks promising. Now we want to use it for a 'next best offer' ML model to integrate with our online storefront.
What you'd have to do today is have a meeting with the data engineering team and explain the logic to them, then have them recreate it in ETL and land it in a database of some sort, then they can pull it into the ML model. There's a ton of waiting.
In an ideal world the BI tool would support pushing to a headless semantic/metric layer that could be directly accessed by your data science team. No engineering intermediary.
Build the strongest roots, allow the most flexibility towards the ends of the branches to grow towards the most nutrient-rich light (insights) as possible. Find the best trunk (metrics) that allows for the most types of branches to grow. Make sure that the ends of the branches have a way to transfer those increasingly nutritious insights back to the roots. Easy enough?
Haha, you nailed it!
When is part 3 coming out?
Can you think of an example of discovering a new insight/metric during exploration/discovery and then what the current as-is state would be to export out or push that insight back down to ML/AI apps, or even a new dashboard?
Yeah, imagine I'm using Tableau to do what they used to call 'visual data discovery' and I do a market segmentation that looks promising. Now we want to use it for a 'next best offer' ML model to integrate with our online storefront.
What you'd have to do today is have a meeting with the data engineering team and explain the logic to them, then have them recreate it in ETL and land it in a database of some sort, then they can pull it into the ML model. There's a ton of waiting.
In an ideal world the BI tool would support pushing to a headless semantic/metric layer that could be directly accessed by your data science team. No engineering intermediary.