Four Ways To Optimize Cloud Data Lake Cost

September 17, 2020

Conducting ad-hoc analytics, streaming analytics and machine learning workloads in the cloud offers unique cost, performance, speed, time to value, and accessibility advantages. However, data in the cloud also means greater unpredictability of both workload sizes and the associated costs. Before you know it, your costs can spiral out of control — and you may not notice until the problem gets out of hand. Join Balaji Mohanam, Director Product Management, and Dhiraj Sehgal, Director Product Marketing, to hear about 4 ways an open data lake architecture provides the capabilities and sustainable economics needed to adequately control your data processing costs.

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