If 2018 was about anything, it was about preparing big data for its next big phase. After several years of being stalled, stymied, and even charged with being one big bust, big data is about to live up to its hype. Many of the CDOs and other data professionals I’ve spoken with in recent months agree we’re on the cusp of something truly “big.” These are the same organizations that have continued to make big investments in data, learning from their mistakes, applying those lessons, and adopting the technologies that are allowing them to blow past many of their remaining obstacles. It’s this new optimism, investment, and innovation that’s bringing about the actual execution everyone’s been expecting for some time now, and it’s the same trifecta of opportunity that’s behind my top five big data predictions for 2019.
#5: Now Proven, AI and ML Will Dig Deeper Into Enterprise
In 2018, we watched as the time, cost, and labor-intensive manual processes that have been holding up the big data initiatives within organizations began to melt away. Automation, AI, and ML — proven now not just in terms of speed, but also accuracy — is now being applied to more and more business functions. This fits into a general trend of moving away from hard-coding business process and operations into software — and adjusting people and physical operations to match the predefined and rigid business processes — and toward dynamically adapting business processes and operations to the physical realities and historical learnings. For example, universities are measuring historical admission and acceptance trends to determine who is likely to accept admission and how much scholarships would affect their decision. Alternative credit risk analysis is being performed to determine the creditworthiness of first-time or low-income borrowers. Customer churn predictions are being gleaned from sentiment analysis of social media. Key to all these applications is the ability to create good stable models and the key to building good stable models is being able to find the right data and create the right features. In 2019, AI and ML will play a big role in finding and understanding the data needed to build those models.
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