Research universal data models. Find articles on universal (or packaged, industry, or functional area) data models, or find information on some commercial offerings. Identify common features across...

Universal data models
Universal data models are defined as the data models that describe the data of the organization in a simple and meaningful way such as objects, requirement, function, purpose, relation and state etc. UML (unified modeling language) that is used to model the relationship between the different entities and arrays are also used as universal data model by the different companies to store the multimodal data (Ding, Xu, Pan & Li, 2021). The companies are using these kind of data models to manage the risks related to poor readability and description of data, it help to provide the value added services and quality of service to the different customers. The data problems of numerous data can be resolved easily by the use of array as a universal data model, array is an efficient data modal that can be used to store the data of any type. A database can be built by the use of this model that can process all the data such as images, tables, video, genomics, metadata, features, LiDAR, mflat files (Guns, 2022). A universal database can be built up by the use of array or multidimensional arrays. There are several advantages of using different data models such as data diversity, vendor optimization and holistic governance. There are different methods of using the arrays that help to store the multimodal data such as dense array and sparse array. Dense arrays can have any number of dimensions and sparse arrays are different as compared to dense arrays. In case of sparse arrays cells of the arrays can be empty; the heterogonous dimensions are there in sparse arrays including strings, floats etc. In this type of array cell multiplicity is also allowed that is not available in dense array (Henry et al., 2021). Following are the multiple uses of multidimensional arrays:
Arrays are used...