Define the terms "ETL" (Extract, Transform, Load) and "data cleansing" in the context of data management.
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Define the terms "ETL" (Extract, Transform, Load) and "data cleansing" in the context of data management.
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- Explain the concept of data masking and anonymization in data warehousing, emphasizing their role in protecting sensitive information.The administration of master data in databases, often known as MDM, may take many different forms.Explain the concept of data carving in the context of data recovery.
- Explain the concept of "microchip-based data encryption" in the context of data security within a data warehouse.Recovery of databases may be performed in both forward and backward directions.Explain the concept of data replication in DDBMS. What are the strategies for managing data replication and ensuring consistency?
- Explain the concept of asset tagging in database security and how it contributes to data protection.Explain the concept of data replication in database management. What are the reasons for replicating data, and what strategies can be used to achieve high availability and fault tolerance?Explain the concept of data virtualization in the context of data warehousing.
- Define the concept of data warehousing and its primary objectives in the field of data management.For what purposes does data management exist?Explain the concept of data archiving and its significance in data management. What criteria should organizations consider when deciding what data to archive?