2030, Decision Analytics and Deep Learning

Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

SEPTEMBER 23, 2020

billion by 2030. Type of Data: structured and unstructured from different sources of data Purpose: Cost-efficient big data storage Users: Engineers and scientists Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning Sizes: Store data which might be utilized.

Data Lake

Data Lake Data Warehouse Unstructured Data Big Data

Data Leaders Brief

Differentiating Between Data Lakes and Data Warehouses

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