Big data, or massive data sets that can be used to make inferences and reveal patterns, has become an increasingly important part of modern business and can be leveraged in many different ways. There are a few different options for storing this data available, which the use case for the data will dictate. Here, we’ll evaluate whether a “data lake” or a “data warehouse” would better suit your needs.
Data Lakes Compared to Data Warehouses
Structure
The difference between data lakes and data warehouses is pretty well described by their names. Much like a real-life lake, a data lake is effectively a catch-all mix of the entirety of its contents, while the data warehouse is very much like a real warehouse is (or should be): organized, and only containing what is necessary to store.
Due to these differences, a data lake and a data warehouse hold raw and processed data, respectively.
Who Puts These Storage Options to Use?
The difference in structure that these two storage systems present makes them more useful in much different use cases. Business users, who need specific and organized data with clear and practical utility, benefit from the structure of a data warehouse. A data lake tends to be of the most use to a data scientist, as they can see the big picture and use their skills to draw conclusions from the mess of information present.
What is the Solution For?
Data lakes, as the name would suggest, are very large. As a result, they are ideal for storage. Their unstructured nature also lends itself well to data analytics, as our hypothetical data scientist will attest to. The structure present in the data warehouse makes them the better choice for drawing insights from aggregated data.
Lake, Warehouse, or Both?
In many cases, the most benefit is to be had by leveraging both of these options. The massive amount of unstructured data in the data lake helps with machine learning processes, and data warehouses lend themselves well to business analytics. Your particular industry can also play a role. Industries that produce massive amounts of data with no real structure, like healthcare and education, might see the most benefit from the size of a data lake. Businesses that operate in the financial industry and other industries like it might find the data warehouse better for their needs, with its optimized accessibility lending itself to their processes.
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