In this article authors focused on the role of decision intelligence in closing the “last mile” gap between current technologies and the value large organizations seek to extract from their data analytics investments. By diwo.ai.
Decision intelligence (DI) is the ability to use relevant and available data to identify and explain optimal actions that improve business outcomes.
We live in a world where there is so much data available, and it is growing non-stop. By 2025, there will be ~ 128 zbs of data. The average employee today is simultaneously engulfed by data and yet unable to find the most important data to make the best decisions in real time. So businesses have data, but lack insights to efficiently bridge the gap from data to decisions—what is commonly referred to as the “last mile of analytics challenge.” Companies won’t realize the full promise of data analytics until they operationalize the “last mile” step where insights become actionable. The path to ROI with analytics is better decisions, not better dashboards.
The article is split into:
- Can decision intelligence solve the last mile of analytics challenge?
- How can decision intelligence help more people improve decision-making in the daily routine of their jobs?
- Where should decision intelligence be used?
- How does decision intelligence fit into the modern data stack?
In its simplest form, a modern data stack encompasses an ingestion tool, a warehousing tool, a transformation tool, analysis and model building tools and the “decision” layer built on the advanced analytical capabilities of decision intelligence. Each of these layers play a key role in an organization’s ability to get actionable insight from vast amounts of data and ML models, develop recommendations for action and accelerate decision-making. Good read!
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