The index that stores records in a tabular format is columnstore. A columnstore index is a type of index that stores and compresses data by columns rather than by rows. A columnstore index can improve the performance and efficiency of queries that perform aggregations, calculations, or analysis on large amounts of data, such as data warehouse or business intelligence applications. A columnstore index can also reduce the storage space required for data by applying various compression techniques, such as dictionary encoding, run-length encoding, bit packing, etc. The other options are either different types of indexes or not related to indexes at all. For example, a non-clustered index is a type of index that stores the values of one or more columns in a sorted order along with pointers to the corresponding rows in the table; a unique index is a type of index that enforces uniqueness on one or more columns in a table; a secondary index is an alternative term for a non-clustered index. References: CompTIA DataSys+ Course Outline, Domain 3.0 Database Management and Maintenance, Objective 3.1 Given a scenario, perform common database maintenance tasks.

The correct answer is C. SQL injection. According to CompTIA DataSys+ objectives, web-based input mechanisms such as contact forms and online surveys represent a significant attack surface for databases if they are not properly secured. These forms commonly accept user-supplied input that is later processed by backend database queries. If input validation and parameterized queries are not correctly implemented, attackers can exploit this by injecting malicious SQL code into form fields.

SQL injection attacks allow an attacker to manipulate database queries executed by the application. This can result in unauthorized access to sensitive data, data modification, data deletion, or even full database compromise. In a healthcare environment, this risk is especially critical because patient data is highly sensitive and often protected by regulatory requirements. DataSys+ highlights SQL injection as one of the most common and dangerous database-focused attacks due to its direct impact on data confidentiality, integrity, and availability.

Option A, Denial of Service (DoS), primarily affects system availability by overwhelming resources, but it does not directly target data stored within the database. Option B, ransomware, typically requires malware execution on servers or endpoints and is not specifically tied to web form input mechanisms. Option D, brute-force attacks, focus on repeatedly guessing authentication credentials and are more closely associated with login systems rather than data entry forms or surveys.

CompTIA DataSys+ materials emphasize that databases connected to web applications must use strong input validation, stored procedures, prepared statements, and least-privilege database accounts to mitigate SQL injection risks. Because contact forms and surveys directly interact with database queries and rely on untrusted user input, SQL injection represents the most direct and realistic threat in this scenario.

Therefore, SQL injection is the attack type to which the company’s data is most vulnerable, making option C the verified and correct answer.

The correct answers are D. It can contain more than one data file and F. It can be used to organize data in a database. CompTIA DataSys+ describes a tablespace as a logical storage container used by a database to organize how data is physically stored on disk. Tablespaces provide an abstraction layer between the logical database objects and the physical storage files.

A tablespace can include multiple data files, which allows database administrators to distribute data across different disks or storage systems. This capability supports scalability, performance optimization, and high availability. By adding or resizing data files within a tablespace, administrators can expand storage capacity without restructuring the database schema. DataSys+ highlights this as a key advantage for capacity planning and storage management.

Tablespaces are also used to organize data within a database. Different tablespaces can be created for different purposes, such as separating user data, indexes, temporary data, and system metadata. This organization improves performance tuning, simplifies backup and recovery operations, and enhances manageability. For example, placing indexes in a separate tablespace from table data can reduce I/O contention.

Option A is incorrect because a tablespace belongs to a single database and cannot span multiple databases. Option B is misleading; while tablespaces map to data files, blocks are allocated within files, not mixed arbitrarily across files. Option C is incorrect because segments are allocated in extents, and their sizing behavior is controlled by storage parameters, not defined as a primary purpose of tablespaces. Option E is incorrect because tablespaces represent disk-based storage, not memory-resident structures.

CompTIA DataSys+ emphasizes understanding logical versus physical storage concepts. Tablespaces play a central role in bridging these concepts by organizing data logically while enabling flexible physical storage management. Therefore, the best descriptions of a tablespace are D and F, making them the correct and verified answers.

The script that would set the database recovery model for sys.database is option A. This script uses the ALTER DATABASE statement to modify the recovery model of the sys.database to full with no wait. The other options either have syntax errors, use incorrect keywords, or do not specify the recovery model correctly. References: CompTIA DataSys+ Course Outline, Domain 3.0 Database Management and Maintenance, Objective 3.1 Given a scenario, perform common database maintenance tasks.

The correct answer is B. Checkpoints. CompTIA DataSys+ explains that checkpoints play a critical role in database recovery mechanisms by limiting the amount of transaction log data that must be processed during recovery. Log-based recovery relies on transaction logs to restore the database to a consistent state after a failure. If checkpoints are infrequent, the database engine must replay a large portion of the transaction log, which increases recovery time and system overhead.

A checkpoint is a process where the database writes all modified (dirty) pages from memory to disk and records a synchronization point in the transaction log. After a checkpoint completes, the database knows that all changes up to that point are safely stored on disk. During recovery, the system only needs to process log entries that occurred after the most recent checkpoint, significantly reducing recovery workload and time. DataSys+ highlights checkpoints as a key performance and availability feature, especially in systems with high transaction volumes.

Option A, deadlocks, are concurrency issues that occur when two or more transactions block each other indefinitely. While deadlock handling is important for transaction throughput, it does not reduce log-based recovery overhead. Option C, locks, control concurrent access to data and help maintain consistency, but they do not affect how much log data must be replayed during recovery. Option D, indexes, improve query performance but can actually increase logging activity because index changes are also logged.

CompTIA DataSys+ emphasizes that effective recovery planning includes optimizing logging behavior and checkpoint frequency. Properly configured checkpoints strike a balance between runtime performance and recovery efficiency by reducing excessive log replay without causing unnecessary disk I/O.

Therefore, to best mitigate the overhead caused by log-based recoveries, the database manager should use checkpoints, making option B the correct and fully verified answer.

The correct answer is B. 40%. CompTIA DataSys+ explains that Resource Governor is used to manage and allocate CPU and memory resources among multiple workloads or resource pools within a database system. When configuring resource pools, administrators must ensure that the total allocation of minimum resources does not exceed 100%, as all resource pools share the same finite system resources.

In this scenario, the first resource pool has a minimum CPU and memory allocation of 25%, and the second resource pool has a minimum allocation of 35%. Together, these minimum guarantees account for 60% of total available resources. Resource Governor enforces these minimums to ensure that critical workloads always receive their reserved share of system resources, even under heavy load.

The remaining resources are calculated by subtracting the total minimum allocation from 100%.

100% − 60% = 40%

This remaining 40% represents the maximum CPU and memory that can be safely assigned to the third resource pool without violating Resource Governor rules. Assigning a higher value would exceed the total available system resources and would not be permitted under proper configuration guidelines emphasized in DataSys+.

Option A (20%) underutilizes available resources and is unnecessarily restrictive. Option C (60%) and D (100%) are invalid because they would cause the combined minimum allocations to exceed system capacity, leading to misconfiguration or enforcement failures. DataSys+ stresses careful capacity planning when using Resource Governor to balance performance, fairness, and system stability.

Resource Governor is especially useful in multi-tenant or mixed-workload environments, where critical applications must be protected from resource starvation. Proper calculation of minimums and maximums ensures predictable performance and prevents one workload from monopolizing system resources.

Therefore, the correct maximum allocation for the third resource pool is 40%, making option B the correct and fully verified answer aligned with CompTIA DataSys+ guidance.

The first task that the administrator should perform is to create a new service account exclusively for the business intelligence application. This will ensure that the application has the appropriate permissions and credentials to access the company’s transactional data. The other options are either unnecessary, inefficient, or insecure. For example, building a separate data warehouse would require additional resources and time, setting up a nightly FTP data transfer would expose the data to potential breaches, sending the TNS names file would not guarantee that the application can connect to the database, and opening a new port on the database server would create a vulnerability for attackers. References: CompTIA DataSys+ Course Outline, Domain 2.0 Database Deployment, Objective 2.1 Given a scenario, install and configure database software and tools.