As an AI language model, I cannot generate an opinion as dimensionalize is a technical term, but I can provide you with the following definition and information.
Dimensionalize refers to the process of converting data from one system of measurement to another system. In the context of data analysis, dimensionalizing data involves adding dimensions to the data, which allows for deeper analysis and better insights. Dimensions can include characteristics such as location, time, product type, and customer demographics. By adding dimensions to the data, analysts can better understand how these characteristics impact the data being analyzed.
Dimensionalizing data is a common practice in business intelligence and data warehousing. By creating a dimensional model, analysts can more easily visualize and analyze large datasets. This process typically involves mapping data to a concept known as a data cube. A data cube is a multidimensional array that enables analysts to slice and dice data in many different ways.
Overall, dimensionalizing data is an important step towards gaining insights into complex datasets and making data-driven decisions.
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