Data Storage and Operations
Data Storage and Operations involves the design, implementation, and support of stored data to maximize its value from creation to disposal. The key activities include:
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Database Support: Focuses on the data lifecycle, including implementation, backup, and purging.
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Data Technology Management: Defines technical requirements, installs technology, and resolves related issues.
Goals and Principles
Goals
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Data Availability: Manage the accessibility of data throughout its lifecycle.
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Data Integrity: Ensure the accuracy and consistency of data assets.
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Performance Management: Oversee efficient data transactions.
Principles
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Automation Opportunities: Automate processes to reduce errors and rework.
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Reuse: Develop reusable data objects to prevent tight coupling with database schemas.
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Best Practices: Apply best practices in database management.
Subtopics
- Database Administrator (DBA) Roles: Details the responsibilities and tasks of a DBA, including database maintenance, security, performance optimization, and backup management.
- Database Architecture Types: Explores various database architectures such as client-server, cloud-based, and distributed systems.
- Data Processing Types: Describes different methods of processing data, including batch processing, real-time processing, and transactional processing.
- Data Storage Media: Reviews the types of storage media used for databases, from traditional hard drives to modern solid-state drives (SSD) and cloud storage.
- Database Environments: Discusses different environments where databases operate, including development, test, and production settings.
- Common Database Processes: Covers routine processes such as query execution, indexing, transaction management, and data retrieval.
- Resiliency and Recovery: Outlines strategies for ensuring database availability and integrity, including backup techniques, disaster recovery, and failover systems.
- Data Operations Management Principles: Highlights key management principles for effective database operation, including capacity planning, monitoring, and performance tuning.
- Evaluating Data Technology: Provides a framework for assessing different database technologies based on performance, scalability, and cost-effectiveness.