What is one challenge associated with using data lakes?

Data lakes store vast amounts of raw data in its native format until it is needed for analysis. This flexibility allows for the accumulation of diverse data types, but it also leads to a significant challenge: the potential for disorganization. As more data is added without a structured format, it can become increasingly difficult for users to locate and retrieve the specific information they need. This disorganization can hinder efficient data analysis processes and lead to challenges in deriving insights from the data.

In contrast, the other choices do not align with the inherent challenges of data lakes. Data cleaning is not simpler; rather, the abundance of unstructured data often complicates cleaning processes. Due to the nature of data lakes, they typically require substantial storage capacity, contrary to the idea of minimal storage. Finally, while data lakes can provide quick access to vast amounts of data, interpreting the results often becomes more complex rather than quicker and easier, especially when dealing with unprocessed data.