What is a potential drawback of a data lake?

Choosing the option that states a data lake can lead to data silos accurately highlights a significant drawback associated with this architecture. Data lakes are designed to store vast amounts of unprocessed data in various formats, which can make it easy to accumulate and store data. However, this very openness and flexibility can result in disparate data being stored in isolation, leading to data silos.

When organizations use data lakes without implementing proper governance and integration practices, different departments or teams may gather their datasets without sharing them with others. As a result, valuable insights that could be derived from cross-departmental data analysis may be lost. This separation of data can hinder collaboration and make it challenging to achieve a holistic view of the information, impairing decision-making processes.

Ultimately, while data lakes are useful for versatility and scalability, the potential for data silos is a critical concern that organizations must address to ensure they can fully leverage their data assets.