Caserta thought leaders Joe Caserta and Doug Laney were featured in KDnuggets’ annual roundups of data and analytics predictions for 2020 alongside some of the most innovative companies in the AI/Analytics/DS/ML industry. Read their predictions below and click on the links to be taken to the full articles featuring other industry thought leaders.
Joe Caserta’s Predictions for 2020
2019 saw the understanding on the part of business leaders that using the greatest analytic platforms just to create reports was insufficient. 2020 will see the realization of analytics maturity from a people, process, and technology perspective. Organizations will begin to innovate how they do data discovery and business intelligence and will start to use data spiders, bots, artificial intelligence, and NLP to query data and get to insights faster. We are in store for another data revolution that will drastically change the current landscape and turn modern data engineering on its head.
Doug Laney’s Predictions for 2020
The resurgence of AI from its halcyon days in the early ’90s, along with the mainstreaming of data science, has been fueled by nothing other than data. Today big data is “just data”. Its magnitude, even as it continues to swell, no longer overwhelms storage or computing power. At least there’s no longer any excuse that any organization being inhibited by data’s bigness. (Hint: cloud.) Indeed, incrementally improved technologies and techniques have emerged, but the vast availability of data spewing from social media platforms, exchanged among partners, harvested from websites, and dribbling off connected devices has led to unforeseen insights, automation, and optimization. It has also spawned new data-centric business models.
In 2020, I envision (no pun intended, or was it?) extended information ecosystems to arise, further enabling AI and data-science powered digital coordination among business partners. Some organizations may choose to fabricate their own data exchange solutions to monetize their and others’ information assets. Others will fuel their advanced analytics capabilities via blockchain-backed data exchange platforms and/or data aggregators offering an array of alternative data.