HOW CAN ATYPICAL DATA (TEXTS, VIDEOS, IMAGES...) BE EXPLOITED ?
A data lake is the ideal central warehouse for all your polymorphic data due to its ability to store and facilitate the exploitation of heterogeneous and unstructured data.
During the design of a data warehouse, the processing of complex and polymorphic data can be a challenge, especially the ingestion of non-relational data for machine learning projects. When building a Data Warehouse, dealing with complex and polymorphic data could become a challenge, especially non relational data ingestion in machine learning projects. This is when a data lake can be used as a way to maximize the amount and variety of data available for staging in your data warehouse. Data lakes differ from data warehouses by the way data is stored without the need for any transformation. Moreover, data lakes are able to easily collect and store data of any type known as polymorphic (unstructured or semistructured). Data lakes are also better tailored for your data science and advanced analytics projects, like text mining (used in sentiment analysis, user reviews analysis, document summarization, information extraction) or image recognition. Data lakes and data warehouses are not mutually exclusive. They are mostly inclusive and complementary. They allow you to engineer complex data sets and derive unique insights.
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