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Limited database or SQL experience. You need to build foundational knowledge of relational databases, SQL syntax, and database administration concepts before tackling advanced topics.
Week 1Learn database fundamentals: relational vs non-relational models, tables, rows, columns, primary keys, foreign keys, and entity relationships. Install a free RDBMS (PostgreSQL or MySQL)
Week 2Study SQL basics: DDL (CREATE, ALTER, DROP), DML (SELECT, INSERT, UPDATE, DELETE), WHERE clauses, JOINs, GROUP BY, ORDER BY, and aggregate functions
Week 3Learn normalization (1NF through 3NF and BCNF), ACID properties, transactions, stored procedures, triggers, functions, and views
Week 4Study NoSQL database types: document (MongoDB), key-value (DynamoDB), column-oriented (Cassandra), and graph (Neo4j). Understand when to use each type
Week 5Cover Domain 2 (Database Deployment): cloud vs on-premises architecture, IaaS/PaaS/SaaS, schema design (logical, physical, view), data dictionaries, and connectivity concepts
Week 6Study Domain 3 (Database Management): monitoring, performance tuning, index optimization, patch management, load balancing, change management, and documentation
Week 7Cover Domain 4 (Security): encryption at rest and in transit, access controls, least privilege, SQL injection, data masking, GDPR, PCI DSS, and infrastructure security
Week 8Study Domain 5 (Business Continuity): backup types (full, incremental, differential), replication, high availability, log shipping, mirroring, RPO/RTO, and disaster recovery planning
Week 9Take full mock exams across all domains. Review explanations for every incorrect answer. Focus on Domain 3 (25%) and Domain 1 (24%) which together are nearly half the exam
Week 10Final review: practice PBQ-style SQL scenarios, review confusable concepts, re-study any domain where you score below 75%. Schedule your exam
Exam Overview
Format
Up to 90 questions, 90 minutes. Multiple choice, multiple select, drag-and-drop, and performance-based questions (PBQs).
Scoring
Scaled score 100-900. Passing: 700. No penalty for wrong answers -- always guess if unsure.
Domains & Weights
- Database Fundamentals24%
- Database Deployment16%
- Database Management and Maintenance25%
- Data and Database Security23%
- Business Continuity12%
Registration
$369 USD. Available at Pearson VUE testing centers or online proctored from home. Exam fee is $369 USD.
Topic Priority Table
Not all topics are tested equally. Focus your study time on Tier 1 first, then Tier 2. Tier 3 topics rarely appear — just recognize what they do.
Domain 124% of exam
Database Fundamentals
This domain covers core database concepts, SQL programming, scripting, and the impact of application code on databases. You need to understand relational and non-relational database types, write and interpret SQL using DDL/DML/TCL, and understand normalization, ACID properties, and programming constructs like triggers and stored procedures. At 24% of the exam, this is your SQL knowledge domain.
Key Topics
SQL DDL/DML/TCLACID PropertiesNormalizationRelational DatabasesNoSQL DatabasesStored ProceduresTriggersViewsORM Tools
Must-Know Concepts
- Relational database structures: tables, rows, columns, primary keys, foreign keys, composite keys, and entity relationships including cardinality (one-to-one, one-to-many, many-to-many)
- Non-relational database types: Document (MongoDB, Cosmos DB), Key-Value (DynamoDB), Column-Oriented (Cassandra), Graph (Neo4j) -- know when to use each type
- DDL commands: CREATE, ALTER, DROP, TRUNCATE -- used to define and modify database structure
- DML commands: SELECT, INSERT, UPDATE, DELETE -- used to manipulate data. Must know JOINs (INNER, LEFT, RIGHT, FULL), WHERE, GROUP BY, HAVING, ORDER BY, and aggregate functions
- Transaction Control Language (TCL): COMMIT, ROLLBACK, SAVEPOINT -- used to manage transactions
- ACID properties: Atomicity (all or nothing), Consistency (valid state), Isolation (concurrent independence), Durability (permanent commits)
- Normalization: 1NF (atomic values, no repeating groups), 2NF (no partial dependencies), 3NF (no transitive dependencies), BCNF (every determinant is a candidate key)
- Programming constructs: Triggers (auto-execute on events), Stored Procedures (reusable code blocks), Functions (return values), Views (virtual tables from queries)
- ORM tools (Hibernate, Entity Framework, Ebean): understand how they abstract SQL and their performance implications
- Scripting: PowerShell, Python, and command-line scripting (Linux/Windows) for database automation. Server-side vs client-side execution
- ANSI SQL standards and set-based logic for writing efficient queries
Common Exam Traps
DDL modifies STRUCTURE (tables, schemas). DML modifies DATA (rows). TCL manages TRANSACTIONS. The exam tests whether you can classify SQL statements correctly
TRUNCATE is DDL, not DML, even though it removes data -- it resets the table structure. DELETE is DML because it removes specific rows
A view is a virtual table based on a query -- it does not store data. A materialized view DOES store data physically and must be refreshed
Normalization reduces redundancy but can hurt read performance. Denormalization improves reads but increases redundancy. The exam tests trade-offs, not just theory
NoSQL does NOT mean 'no SQL.' Many NoSQL databases support SQL-like query languages. The distinction is about data models and schema flexibility, not query language
Domain 216% of exam
Database Deployment
This domain covers planning, designing, implementing, testing, and deploying databases. You must understand how to choose between cloud and on-premises architectures, design schemas at logical and physical levels, document database designs, and validate deployments through comprehensive testing. At 16%, this is the smallest technical domain but critical for design scenarios.
Key Topics
Schema DesignCloud ArchitectureIaaS/PaaS/SaaSData DictionariesEntity RelationshipsConnectivityTesting
Must-Know Concepts
- Requirements gathering: user count, storage capacity, database objectives, and growth projections
- Architecture decisions: cloud vs on-premises vs hybrid. Cloud models: IaaS (you manage DB), PaaS (managed platform like AWS RDS or Azure SQL), SaaS (fully managed)
- Schema types: Logical schema (business view, entities and relationships), Physical schema (actual implementation, tables and columns), View schema (user-facing perspective)
- Documentation: Data dictionaries (metadata repository), Entity relationships and cardinality, System requirements documents
- Implementation: Asset acquisition, provisioning, and configuration of database servers
- Connectivity: DNS resolution, client/server architecture, firewall rules, IP addressing, ports and protocols relevant to database services
- Testing types: Quality checks, code execution testing, schema validation, stress testing (load capacity), regression testing (changes do not break existing functionality), negative testing (handling invalid input)
- Validation: Index analysis, data mapping, referential integrity verification, and scalability assessment
Common Exam Traps
Logical schema describes WHAT data is stored and relationships. Physical schema describes HOW data is physically stored. Do not confuse the two levels of abstraction
PaaS databases (like AWS RDS) handle infrastructure management for you. IaaS databases (like running PostgreSQL on EC2) require you to manage the OS, patching, and backups yourself
Stress testing and regression testing serve different purposes. Stress testing checks capacity limits. Regression testing ensures changes did not break existing functionality
Referential integrity ensures foreign keys point to valid primary keys. If a question mentions orphan records, the answer involves referential integrity constraints
Negative testing intentionally provides invalid inputs to verify the database handles errors gracefully. It is not the same as finding bugs
Domain 325% of exam
Database Management and Maintenance
The heaviest domain at 25% -- expect roughly 22-23 questions on monitoring, maintenance, documentation, and data management tasks. You must understand system alerts, performance tuning, index optimization, patch management, load balancing, change management, and documentation practices. This is the operational heart of the DBA role.
Key Topics
MonitoringPerformance TuningIndex OptimizationPatch ManagementLoad BalancingChange ManagementDocumentationData Management
Must-Know Concepts
- System alerts and monitoring: growth warnings, usage metrics, throughput, CPU utilization, memory usage, disk I/O, and storage capacity
- Baseline configuration: establishing normal performance metrics to identify deviations and anomalies
- Monitoring targets: job completion status, replication lag, backup success/failure alerts, transaction and system logs
- Connection monitoring: concurrent connections, failed login attempts, and connection pool usage
- Query optimization: analyzing execution plans, identifying slow queries, and rewriting for efficiency
- Index management: creating, rebuilding, and removing indexes based on query patterns and performance analysis
- Patch management: applying security patches and updates with minimal downtime, testing before production deployment
- Database integrity checks: detecting data corruption, table locking techniques, and consistency verification
- Load balancing: distributing database workload across multiple servers for performance and availability
- Change management: release scheduling, capacity planning, upgrade procedures, rollback plans, and approval workflows
- Documentation: data dictionaries, ERDs, standard operating procedures (SOPs), and compliance documentation
- Data management tasks: creating views and materialized views, managing indexes, handling data redundancy, and implementing data sharing
Common Exam Traps
High CPU usage does not always mean a problem -- you must compare against the BASELINE to determine if it is abnormal
Index rebuilding improves read performance but temporarily degrades write performance. Schedule rebuilds during maintenance windows
Materialized views store data physically and must be refreshed. Regular views always reflect current data. The exam tests when each is appropriate
Change management is not just about technical changes. It includes approval workflows, documentation, rollback plans, and communication
Audit log review is a maintenance task, not just a security task. It helps identify performance issues, failed jobs, and operational problems
Domain 423% of exam
Data and Database Security
This domain covers data protection, governance, authentication, authorization, infrastructure security, and attack types. You must understand encryption states, data masking, compliance regulations (GDPR, PCI DSS), access control principles, physical and logical security controls, and the full catalog of database attacks. At 23%, this is the second-heaviest domain.
Key Topics
EncryptionData MaskingAccess ControlsSQL Injection PreventionGDPRPCI DSSInfrastructure SecurityAttack Types
Must-Know Concepts
- Encryption at rest (stored data on disk) and in transit (data moving over the network via TLS/SSL). Know client-side vs server-side encryption
- Data masking: hiding sensitive values while preserving format. Data discovery: identifying where sensitive data exists across systems
- Data destruction techniques: secure deletion methods for decommissioning storage and meeting compliance requirements
- Security audits: reviewing expired accounts, connection request logs, SQL code for vulnerabilities, and credential storage practices
- Governance and compliance: data loss prevention (DLP), data retention policies, data classification (PII, PHI), PCI DSS requirements, GDPR obligations
- Authentication and authorization: user rights, privileges, role-based access, least privilege principle, password policies, service account management, identity and access management (IAM)
- Physical security: access controls, biometrics, surveillance, fire suppression, environmental controls (cooling, humidity)
- Logical security: firewalls, perimeter networks (DMZ), port security, network segmentation
- Attack types: SQL injection, denial of service (DoS), on-path (man-in-the-middle) attacks, brute-force attacks, phishing, and malware including ransomware
- SQL injection prevention: parameterized queries, input validation, stored procedures, and least privilege database accounts
Common Exam Traps
Data masking preserves FORMAT (a masked credit card still looks like a credit card number). Encryption makes data UNREADABLE. They serve different purposes and the exam tests when to use each
GDPR applies to EU personal data regardless of where the organization is located. If you process EU citizen data, GDPR applies to you even if your servers are in the US
PCI DSS applies specifically to payment card data. GDPR applies to all personal data. They can both apply to the same system if it processes EU cardholder information
Service accounts should have dedicated credentials, not shared human accounts. Using personal credentials for automated processes is a security violation
On-path attacks (man-in-the-middle) intercept data IN TRANSIT. Encryption in transit (TLS/SSL) is the primary mitigation, not encryption at rest
Domain 512% of exam
Business Continuity
This domain covers disaster recovery planning, high availability techniques, backup strategies, and restore procedures. Despite being the smallest domain at 12%, it covers critical concepts about keeping databases available and recoverable. Master backup types, replication methods, RPO/RTO, and DR documentation.
Key Topics
Backup TypesReplicationHigh AvailabilityLog ShippingMirroringRPO/RTODisaster Recovery
Must-Know Concepts
- DR documentation types: disaster recovery manuals, security plans, continuity of operations plans (COOP), and build documentation for recreating environments
- Replication: copying data across servers for redundancy. Synchronous replication (zero data loss, higher latency) vs asynchronous replication (some data loss risk, lower latency)
- Log shipping: periodically sending transaction log backups to a standby server. Has built-in delay and typically requires manual failover
- High availability: minimizing downtime through redundancy, failover clusters, and automatic failover mechanisms
- Database mirroring: maintaining a synchronized copy on a mirror server. Can be synchronous or asynchronous. Automatic failover possible with a witness server
- RPO (Recovery Point Objective): maximum acceptable data loss in time. Drives backup frequency
- RTO (Recovery Time Objective): maximum acceptable downtime. Drives DR architecture complexity
- Failback: the process of returning operations to the primary system after a failover event. Must be planned and tested
- Backup types: Full (all data), Incremental (changes since last backup), Differential (changes since last full backup)
- Backup best practices: automation, scheduling, validation (test restores), hash verification, retention policies (purge vs archive), and on-site vs off-site storage
Common Exam Traps
Incremental backup captures changes since the LAST BACKUP OF ANY TYPE. Differential captures changes since the LAST FULL BACKUP. Mixing these up is the most common mistake in Domain 5
Having backups is worthless if you never test restores. The exam specifically tests backup VALIDATION through test restores and hash verification
Failback is NOT the same as failover. Failover switches TO the standby. Failback returns TO the primary. Both must be planned and documented
Off-site backups protect against site-level disasters. On-site backups enable faster restores. A proper strategy uses BOTH
Synchronous replication guarantees zero data loss but adds latency. The exam may present scenarios where latency is a concern and asynchronous replication is the better choice
Concepts You Must Not Confuse
These pairs appear on nearly every exam. Learn the difference and you'll avoid the most common traps.
Top Mistakes to Avoid
Confusing incremental backups (changes since last backup of ANY type) with differential backups (changes since last FULL backup) -- this is the most tested distinction in Domain 5
Mixing up DDL (defines structure: CREATE, ALTER, DROP) with DML (manipulates data: SELECT, INSERT, UPDATE, DELETE) -- TRUNCATE is DDL, not DML
Thinking NoSQL means the database cannot use SQL -- many NoSQL databases support SQL-like query languages. The distinction is about data models, not query languages
Confusing authentication (verifying identity) with authorization (granting permissions) -- authentication must happen before authorization
Not knowing the difference between views (virtual, always current) and materialized views (physical, must be refreshed) -- the exam tests when each is appropriate
Applying patches directly to production without testing in a non-production environment first -- this violates change management best practices
Confusing RPO (maximum acceptable data loss) with RTO (maximum acceptable downtime) -- both are measured in time but measure fundamentally different things
Thinking more indexes always improve performance -- indexes speed up reads but slow down writes because every INSERT, UPDATE, and DELETE must update all indexes
Confusing data masking (preserves format, for non-production use) with encryption (makes data unreadable, for production data protection)
Forgetting that GDPR applies based on the data subject's location, not the server location -- processing EU data in US servers still requires GDPR compliance
Exam-Ready Checklist
Can explain all 5 exam domains and their relative weights (24%, 16%, 25%, 23%, 12%)
Can write and interpret SQL statements: DDL, DML, TCL, JOINs, subqueries, aggregate functions, and GROUP BY/HAVING
Understand normalization through 3NF and BCNF -- can identify which normal form a table violates and how to fix it
Know all four NoSQL database types (document, key-value, column-oriented, graph) and when to use each
Can explain ACID properties and why each matters for transaction reliability
Understand all three backup types (full, incremental, differential) and can recommend the right strategy based on RPO/RTO requirements
Can distinguish between encryption at rest and in transit, and know when each applies
Know SQL injection attack mechanics and prevention methods (parameterized queries, input validation, least privilege)
Understand authentication vs authorization and can apply the least privilege principle in access control scenarios
Can explain high availability techniques: replication (synchronous vs asynchronous), log shipping, mirroring, and failover/failback
Know GDPR and PCI DSS requirements and which types of data each regulation protects
Understand change management process: testing, approval, documentation, rollback planning, and communication
Scored 75%+ on at least two full mock exams (700/900 passing score)
Practiced PBQ-style scenarios: writing SQL queries, analyzing execution plans, and troubleshooting database issues
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