Illustration by Agnes Jonas
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In private equity and venture capital, firms have invested in using external data sources often referred to as “alternative data,” a broad term used to describe information sourced from outside a company’s internal systems, including social media chatter, news feeds, government reports, industry databases, anonymized credit card transactions, and satellite imagery. For private investors eager to stay on the cutting edge, there are significant opportunities: from identifying potential investment opportunities and conducting due diligence, to adding value post-investment. While these approaches have been honed by investors, they also offer models for how companies across industries can use alternative data.
Over the past year or so, it’s been hard to escape the impression that AI is becoming a massive disruptive force. AI, of course, is only as good as its data, and thus far the data sources undergirding the AI revolution haven’t been used to their full potential. Making good use of AI and machine-learning tools often entails having the right data strategy to support them.
