CompTIA Updated DS0-001 Exam Questions and Answers by maksymilian

The SQL command that the administrator should use to ensure that records from the two tables are not duplicated is option A. This command uses the UNION clause to combine the records from the legacy table and the newer table into a single result set. The UNION clause also eliminates any duplicate records that may exist in both tables, and sorts the result by default. The other options either do not produce the desired result or have syntax errors. For example, option B would join the records from the two tables based on a common column, but not remove any duplicates; option C would return only the records that are common to both tables, but not the ones that are unique to each table; option D would produce a Cartesian product of the records from the two tables, which would increase the number of duplicates. References: CompTIA DataSys+ Course Outline, Domain 1.0 Database Fundamentals, Objective 1.2 Given a scenario, execute database tasks using scripting and programming languages.

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 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. To specify how data is sorted in a database. CompTIA DataSys+ explains that the COLLATE clause defines the collation rules applied to character-based data in a column. Collation determines how string data is compared, sorted, and evaluated, including rules for alphabetical order, case sensitivity, accent sensitivity, and character encoding. These rules directly affect query results, indexing behavior, and comparison operations involving textual data.

When a COLLATE clause is included in a column definition, it overrides the database or server default collation for that specific column. This is especially important in environments that support multiple languages or regional settings, where sorting and comparison rules may differ. For example, case-insensitive collations treat uppercase and lowercase letters as equivalent, while case-sensitive collations do not. DataSys+ highlights that incorrect collation settings can lead to unexpected query results, inefficient indexing, or inconsistent application behavior.

Option A is incorrect because computed columns and indexing behavior are defined through expressions and index definitions, not collation rules. Option C, functional dependency, relates to normalization theory and the relationship between attributes in a relational schema; collation has no impact on dependency enforcement. Option D describes data validation, which is handled through constraints such as CHECK, NOT NULL, or data types—not collation.

CompTIA DataSys+ emphasizes that DBAs must understand how collation affects sorting, grouping, and comparison operations, especially for reporting and internationalized applications. Proper use of the COLLATE clause ensures consistent behavior across queries and prevents subtle bugs related to string comparisons.

Therefore, the primary purpose of including a COLLATE clause in a column definition is to control how textual data is sorted and compared, making option B the correct and verified answer.