Evolving Data Infrastructure
Tools and Best Practices for Advanced Analytics and AI
How are companies using or exploring AI, big data, and the cloud for advanced analytics and automation? In an O’Reilly survey conducted in October 2018, more than 3,200 companies throughout the world—located primarily in North America, Europe, and Asia—revealed their choices of tools, technologies, and practices for pursuing sophisticated cloud-based data solutions.
In this report, data science experts Ben Lorica and Paco Nathan break down the results of the survey to reveal how companies are using, building, or evaluating data infrastructure in the cloud. One group of respondents has had a cloud-based data infrastructure for years, while a second group is still exploring the possibilities. Early adopters currently building a cloud-based data infrastructure represent the largest of these three groups.
This report reveals:
- Foundational data technologies (ETL, data prep, data governance, etc.) that respondents consider most critical for success in machine learning and AI
- High demand for data scientists and engineers to fill skills gaps
- How companies use more than one cloud provider to build data infrastructure
- Streaming and data processing technologies these companies use most
- The mix of open source and managed services respondents use for business intelligence
- How many companies are using serverless technologies for data science and machine learning
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