Written by Jason Bailey
The excellent “Annual Big Data Executive Survey 2018” from New Vantage Partners confirms several important trends and issues that we at Tamr are seeing daily out in the field. Most notably is a dramatic increase in investment in AI projects by Fortune 1000 companies driven by fear of disruption from agile data-driven upstarts. According to the survey:
- Firms fearing disruption from agile data-driven upstarts jumped from 46.6% to 79.4% from 2017 to 2018
- 97.2% of executives are investing in, launching, or building AI initiatives
- 72% executives judged AI “most disruptive technology” vs cloud computing (13%), and blockchain (7%)
What we often see at Tamr is that large enterprises put the cart before the horse and pursue AI initiatives before tackling the less sexy tasks of preparing and unifying their enterprise data. Unlike smaller companies that have less data and have built data driven cultures from the ground up, large enterprises must first prepare and unify siloed legacy data to see the results they are looking for from AI projects. As Tamr CEO Andy Palmer has stated “The common thread unifying successful digital transformation programs and early wins from AI initiatives is that they start by unifying their core data from their many, many source systems.” Evidence of the poor results that come with running projects on messy siloed data is manifested is the low success rates visible in the survey. Just 23.9% of executives participating in the survey characterize their results from Big Data and AI as highly transformative and innovative.
Creating complete, accurate, easily accessible views of the things that matter most to a business — customers, suppliers, products, employees, etc.– is the necessary foundation upon which success is built. The advice we give most to large enterprise customers is to get your data right first, capture early, impactful wins, increase DataOps maturity and then start integrating bright, shiny tech.
If you would like to learn more about how Tamr uses AI and Machine learning to help enterprises like GE, GSK, and Toyota Motors Europe unify their data for analytical insights and to drive successful AI projects internally, sign up for a live demo.