Data has increasingly become a critical component of just about every aspect of business and the amount of data is skyrocketing. In fact, 90% of the world’s data has been created in the last 2 years and it's expected that by 2020, 463 exabytes of data will be created every day from wearables, social media networks, communications (business and consumer), transactions and connected devices. While the explosion in the volume -- and more importantly, diversity of data -- is instrumental in supporting the future of artificial intelligence (AI) and accelerates the automation of data analysis, it's also creating the obstacles that enterprises currently face in their adoption of AI.
In order to understand these obstacles, Trifacta launched a benchmark report in conjunction with Researchscape: Obstacles to AI & Analytics Adoption in the Cloud, to examine how data workers in the U.S. across industries are handling the increased move of data to the cloud, the time constraints endured when preparing data for analytics, artificial intelligence and machine learning initiatives, and the impact these obstacles have on the overall success of these projects.
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