Business Intelligence (BI) is a $23 billion market and a cornerstone of data-driven decision-making. Artificial intelligence (AI) is a $21 billion market quickly becoming a central part of an effective data strategy. However, both markets depend on a category of software you probably haven’t heard of: data intelligence.
According to market researcher IDC, data intelligence ensures that BI and AI are powered by “trustworthy and reliable data”. In other words, data intelligence helps solve the garbage in-and-out problem that causes BI and AI initiatives to fail and fail.
Data intelligence for BI and AI
Incoming and outgoing waste has always been a problem for BI, and today, the changing regulatory environment has made the situation even more apparent. Not only do BI users need to care about data quality and accuracy, but they also need to understand and adhere to policies and guidelines. The salvation of BI is the human element involved. If a dashboard shows inaccuracies or draws the wrong conclusions, the onus is on a human to intervene – obviously not optimal, but doable.
Conversely, AI does not rely on this human element. When the AI is fed incorrect or inferior data, this human safety net is not there to correct errors. And given the scalability that AI offers, it’s likely that this mistake will continually repeat itself, often causing irreparable damage. For all its strength, the AI suffers exponentially from incoming and outgoing garbage – it behaves more like incoming garbage, dumps. Data Intelligence
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