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CompTIA DS0-001 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Database Management and Maintenance: Here, you'll learn about monitoring and reporting for database management and performance, common database maintenance processes, documentation production, and relevant tools usage. Lastly, the topic focuses on implementing data management tasks.
Topic 2
  • Business Continuity: Finally, this topic covers the importance of disaster recovery techniques. Moreover, the topic explains backup and restore best practices and processes.
Topic 3
  • Data and Database Security: This topic focuses on data security concepts, governance and regulatory compliance purposes, implementing authentication and authorization policies and best practices. Additionally, the topic discusses database infrastructure security, and understanding types of attacks and their effects on data systems.
Topic 4
  • Database Fundamentals: This topic covers database structure types, SQL code development and modification based on scenarios, comparison of scripting methods and environments, and the impact of programming on database operations.
Topic 5
  • Database Deployment: In this topic, you'll find discussions on database planning and design aspects. It also focuses on the implementation, testing, and deployment phases of databases.

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CompTIA DataSys+ Certification Exam Sample Questions (Q34-Q39):

NEW QUESTION # 34
Which of the following are ORM tools? (Choose two.)

Answer: B,E


NEW QUESTION # 35
As part of an integrity check, a database administrator is creating both the primary and secondary snapshots. The database administrator notices the primary replica is failing over to the secondary replica. Which of the following describes how this will affect the database?

Answer: A

Explanation:
Failover from a primary to a secondary replica in a properly configured environment is designed to be seamless, maintaining database availability and integrity without impacting operations.


NEW QUESTION # 36
Which of the following NFs is considered the most preferable for relational database design?

Answer: B

Explanation:
The NF (normal form) that is considered the most preferable for relational database design is 3 NF. 3 NF, or Third Normal Form, is a level of normalization that organizes data into tables and columns to reduce redundancy and improve consistency. Normalization is a process that applies a set of rules or criteria to eliminate or minimize the anomalies or problems that may arise from inserting, updating, or deleting data in a database. 3 NF is achieved when a table satisfies the following conditions: - It is in 2 NF (Second Normal Form), which means that every non-key column depends on the whole primary key and not on any subset of it
- It has no transitive dependencies, which means that every non-key column depends directly on the primary key and not on any other non-key column 3 NF is considered the most preferable for relational database design because it ensures that each table has only one purpose or theme and that each column has only one value or meaning. This helps avoid data duplication, inconsistency, and update anomalies. The other options are either lower or higher levels of normalization that are either less preferable or less practical for relational database design. For example, 1 NF (First Normal Form) is the lowest level of normalization that requires each column to have atomic values and each row to have a unique identifier; 4 NF (Fourth Normal Form) is a higher level of normalization that requires each table to have no multi-valued dependencies, which means that there are no columns that can have more than one value for the same primary key value; 2 NF (Second Normal Form) is an intermediate level of normalization that requires each non-key column to depend on the whole primary key and not on any subset of it. References: CompTIA DataSys+ Course Outline, Domain 1.0 Database Fundamentals, Objective 1.2 Given a scenario, execute database tasks using scripting and programming languages.


NEW QUESTION # 37
Which of the following sets the age requirement for data that should be recovered after a major disaster?

Answer: C

Explanation:
The option that sets the age requirement for data that should be recovered after a major disaster is RPO. RPO, or Recovery Point Objective, is a metric that defines the maximum amount of data that can be lost or acceptable data loss in the event of a disaster or disruption. RPO indicates how frequently the data should be backed up or replicated to minimize the risk of data loss. RPO also sets the age requirement for data that should be recovered after a major disaster, as it determines how far back in time the recovery process should go. For example, if the RPO is one hour, then the data should be backed up or replicated every hour, and the recovery process should restore the data to the state it was in one hour before the disaster. The other options are either different metrics or not related to data recovery at all. For example, MTBF, or Mean Time Between Failures, is a metric that measures the average time that a system or component operates without failure; RTO, or Recovery Time Objective, is a metric that defines the maximum amount of time that can be taken to restore a system or service after a disaster or disruption; MTTF, or Mean Time To Failure, is a metric that measures the average time that a system or component operates until it fails.


NEW QUESTION # 38
A database administrator is concerned about transactions in case the system fails. Which of the following properties addresses this concern?

Answer: A

Explanation:
The property that addresses this concern is durability. Durability is one of the four properties (ACID) that ensure reliable transactions in a database system. Durability means that once a transaction has been committed, its effects are permanent and will not be lost in case of system failure, power outage, crash, etc. Durability can be achieved by using techniques such as write- ahead logging, checkpoints, backup and recovery, etc. The other options are either not related or not specific to this concern. For example, isolation means that concurrent transactions do not interfere with each other and produce consistent results; atomicity means that a transaction is either executed as a whole or not at all; consistency means that a transaction preserves the validity and integrity of the data.


NEW QUESTION # 39
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