Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

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.

Winning the Future: Digital Transformation, the Cloud, and AWS

Sisense

Enabling data-driven decisions throughout the company (not just in certain departments or teams) 2. You know your company has a lot of data, but are you using it to make smarter decisions? Choose the right cloud; choose the right analytics partner and thrive.