The data lake is an important piece of a modern data strategy—especially when it comes to supporting a wide variety of data types and more advanced analytics.

Today’s data lakes are often built on cloud-based object stores that run on public, private, hybrid, and other cloud architectures to provide scalability and extensibility. These modern data lakes support SQL, artificial intelligence (AI), machine learning (ML), and other advanced analytics.

Modern data lakes also provide an environment with capabilities to load, integrate, and analyze data to derive business value. Some incorporate data catalogs or implement augmented intelligence features such as automatic classification of sensitive data. They automate infrastructure management and provide automated services such as shutting off a job when it is complete. Modern data lakes are often unified or converged with the cloud data warehouse to form a unified platform.

This TDWI Checklist examines important characteristics of the modern data lake and factors to consider to ensure your data lake is future-proof.

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