Artificial intelligence (AI) and machine learning have transformed every industry in some shape or form. When it comes to business intelligence (BI) and data analytics, AI is also driving augmented analytics that makes it easier for any user to analyze volumes of data to accelerate more valuable business insights. This interesting topic came to us from Inside Big Data in their article, “AI-Augmented Analytics is Transforming Business Intelligence and Simplifying Data Complexity.”
Modern data is complex and sometimes difficult to interpret and understand. That’s where a tool like augmented analytics comes in handy. Harnessing machine learning and AI to make data easier to understand seems obvious.
Machine learning capabilities within BI platforms often surface the results of advanced algorithms as recommendations. Additionally, some applications of augmented analytics leverage machine learning to learn industry and organizational semantics, as well as user preferences over time.
Unfortunately, most organizations don’t understand how AI systems make the decisions they do, and as a result, how the results are being applied in the various fields that AI and machine learning are being applied. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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