In racing, you either go fast enough in the first qualifying round, or you don’t race at all. That’s the 107% rule.
It’s like that with big data. Either you have the processing power and performance to meet the scale and speed of big data, or you don’t do big data. No sensor data. No historical data. No unstructured data.
Getting to scale at cost is what modern data engineering is all about. This white paper from Databricks and Talend shows you how to use intelligent and automated cloud tools to scale big data and operationalize machine learning. That means you can process more data, faster, for better insight, using the same budget and skillsets.
Download now for a guide to:
- Lower operational costs and increase agility with less complexity
- Scale cloud resources automatically so you only pay for what you use
- Easily spin up experiments, apply machine learning, and gain new insight
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