Databases Practice Exam

A database refers to a software which stores data in a structured manner so that data can be easily accessed, managed, and updated. Databases help to store and organize data as well as provide features to maintain security, data integrity and availability. They are used across industries and can be relational (SQL-based) or non-relational (NoSQL-based).

A certification in Databases certifies your skills and knowledge in managing, designing, and implementing databases. This certification assess you in database architecture, optimization, and security.
Why is Databases certification important?

• Demonstrates proficiency in database design, management, and optimization.
• Boosts job prospects in data-driven industries.
• Shows mastery of tools like SQL Server, Oracle, or MongoDB.
• Opens opportunities for advanced database administration or architecture roles.
• Ensures skills in optimizing queries and managing large datasets.
• Validates knowledge of database security practices and compliance.
• Equips candidates to work with cloud-based and distributed databases.
• Certifications are valued by employers worldwide.
  

Who should take the Databases Exam?

• Database Administrator (DBA)
• Data Analyst
• Data Engineer
• Software Developer
• IT System Administrator
• Cloud Engineer
• Business Intelligence (BI) Developer
• Data Scientist
• Application Developer
• Database Architect

Skills Evaluated

Candidates taking the certification exam on the Databases is evaluated for the following skills:

• Database Design and Modeling
• Querying and Data Manipulation
• Database Administration
• Performance Optimization
• Security Practices
• Data Integration
• Cloud Database Management
• Troubleshooting
• Database Automation
• Scalability and Maintenance
  

Databases Certification Course Outline
The course outline for Databases certification is as below -

• Types of databases (Relational, NoSQL)
• ACID properties and transaction management

• Entity-Relationship (ER) diagrams
• Normalization and denormalization

• SELECT, INSERT, UPDATE, DELETE commands
• Joins, subqueries, and stored procedures

• NoSQL databases types - document, key-value, graph
• Use cases and limitations

• Backup and recovery
  
• User management

• Indexing
  
• Query optimization
  

• Access control
  
• Encryption
• Data masking

• Cloud-based database services
  
• Migration

• Extract, Transform, Load (ETL)
  
• Data migration and synchronization

• Monitoring
  
• Deadlocks and bottlenecks