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Metadata is crucial in data management because it offers detailed information about the structure, organization, and contents of a dataset, effectively serving as a guide. For customer transactions, metadata may include details like file format, data source, data type, creation date, and author, among others. This context helps analysts understand the dataset’s structure and fields without manually inspecting the data itself, thus expediting data processing and analysis. Metadata is particularly important for ensuring data integrity, facilitating data sharing, and enabling accurate data interpretation, as it reduces the likelihood of errors by providing clear guidelines on dataset usage and attributes. The other options are incorrect because: • Option 1 describes segmentation, which is part of analysis, not metadata. • Option 3 refers to data cleaning and deduplication, unrelated to the descriptive role of metadata. • Option 4 suggests that metadata enlarges the dataset size, which is not its purpose. • Option 5 describes statistical summaries, not metadata, which provides structural information, not analysis results.
In datawarehouse , a fact table consist of
What is the purpose of the #include
What is the primary purpose of virtual memory in an operating system?
Which of the following is a critical component of data protection in both Windows and Unix/Linux environments?
Is every view serializable schedule also conflict serializable?
Which represents a collection of binary data stored as a single entity in the database management system?
State True or False
Kernel level thread cannot share the code segment.
Which of the following scenarios best demonstrates a potential use of candidate keys in a relational database?
Fill in the correct option for 25 blank space.
In a virtual memory system, which of the following techniques is used to maintain the illusion that each process has its own dedicated memory space?