For instance, unstructured data could be emails with structured information on the date, time, sender and recipient, but the body can comprise anything, including pictures, videos, and text files.Ī data warehouse is a storage solution that keeps structured data from various data sources. Semi-structured data implies having elements of both types of data mentioned above. This can include videos, pictures, and audio files. It doesn’t have a defined framework and is not organized. Unstructured data has not been processed. Some examples include names, dates, geolocation, phone numbers, etc. Structured data is data that has been processed and normalized.

Data lakehouses cover both use cases.īefore we move to the detailed analysis, let’s quickly go through the types of data you can store in your data storage: While data warehouses work well for business intelligence tools, reporting, and charting, data lakes are better for big data analysis and machine learning. Lakehouses can keep structured, semi-structured, and unstructured data, but they also provide a strong metadata management system that allows for keeping the information organized.ĭata lakehouses are easily scalable and less expensive than warehouses. Otherwise, they can very easily become data swamps.ĭata lakehouse is a hybrid data storage solution that takes the best out of both data warehouses and data lakes. On the other hand, because they are not organized, data lakes require strong management. Additionally, it is more affordable and easily scalable than data warehouses. This method enables deep analytics and machine learning. This structure allows for reliable high-quality data but also limits the analytics opportunities because of the predefined schema.ĭata lakes store unstructured and semi-structured data, which allows quick dumping in the storage and then structuring it in accordance with the specific analytical purpose. Different teams within a company, including business analysts, data engineers and marketers, can access the data via BI tools, SQL clients and other analytics applications. data lakehouse - a quick summaryĭata warehouses store already transformed and structured data from multiple sources, such as transactional systems, CRMs, advertising managers, etc.

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