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| Certification Vendor: | CompTIA |
|---|---|
| Exam Name: | CompTIA DataSys+ Certification Exam |
| Exam Number: | DS0-001 |
| Exam Format: | Performance-based, Multiple-choice |
| Passing Score: | 700 (scale 100–900) |
| Related Certifications: | CompTIA Data+ CompTIA Security+ |
| Exam Price: | $246 USD |
| Available Languages: | English, Japanese |
| Exam Duration: | 90 minutes |
| Certificate Validity Period: | 3 years |
| Real Exam Qty: | Up to 90 |
| Recommended Training: | CompTIA DataSys+ Learning Path CompTIA Official Study Guide |
| Exam Registration: | Pearson VUE Testing Center CompTIA Official Registration |
| Sample Questions: | CompTIA DS0-001 Sample Questions |
| Exam Way: | Online proctored or in-person at authorized test centers |
| Pre Condition: | No mandatory prerequisites; recommended 2–3 years of experience in database administration or related roles |
| Official Syllabus URL: | https://www.comptia.org/en/certifications/datasys/ |
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NEW QUESTION # 90
Which of the following is used to write SQL queries in various programming languages?
Answer: A
Explanation:
The option that is used to write SQL queries in various programming languages is object-relational mapping. Object-relational mapping (ORM) is a technique that maps objects in an object-oriented programming language (such as Java, Python, C#, etc.) to tables in a relational database (such as Oracle, MySQL, SQL Server, etc.). ORM allows users to write SQL queries in their preferred programming language without having to deal with the differences or complexities between the two paradigms. ORM also provides users with various benefits such as code reuse, abstraction, validation, etc. The other options are either not related or not effective for this purpose. For example, indexing is a technique that creates data structures that store the values of one or more columns of a table in a sorted order to speed up queries; Excel is a software application that allows users to organize and manipulate data in rows and columns; normalization is a process that organizes data into tables and columns to reduce redundancy and improve consistency. Reference: 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 # 91
Which of the following is the best way to migrate a large data load from one table to another, considering total time and blocking?
Answer: C
Explanation:
The best way to migrate a large data load from one table to another, considering total time and blocking, is to batch into small loads and run in parallel. This means that the large data load is divided into smaller chunks that can be processed simultaneously by multiple threads or processes. This reduces the total time required for the migration and also minimizes the blocking of other operations on the tables involved. The other options are either less efficient or more prone to blocking. For example, splitting the load size into many transactions may increase the overhead and latency of each transaction; splitting the load size in half and running simultaneously may still cause blocking or contention; batching large loads into one transaction may take longer and lock the tables for longer periods. References: CompTIA DataSys+ Course Outline, Domain 3.0 Database Management and Maintenance, Objective 3.3 Given a scenario, migrate data between databases.
NEW QUESTION # 92
Which of the following database structures is a type of NoSQL database?
Answer: A
Explanation:
The database structure that is a type of NoSQL database is key-value stores. Key-value stores are databases that store and manage data as pairs of keys and values. Keys are unique identifiers that locate data in the database; values are arbitrary data that can be any type or format. Key-value stores do not use any schema or structure to organize data, but rather use hash tables or indexes to enable fast and simple access to data based on keys. Key-value stores are suitable for storing large amounts of simple or unstructured data that do not require complex queries or relationships. The other options are either different types of databases or not related to database structures at all. For example, hierarchical databases are databases that store and manage data as nodes in a tree-like structure; cloud databases are databases that are hosted and accessed over the internet using cloud computing services; object-oriented databases are databases that store and manage data as objects that have attributes and methods. Reference: CompTIA DataSys+ Course Outline, Domain 1.0 Database Fundamentals, Objective 1.1 Given a scenario, identify common database types.
NEW QUESTION # 93
(Which of the following is used to store product quantities in a table while ensuring the minimal amount of storage is consumed?)
Answer: C
Explanation:
The correct answer is B. INTEGER. According to CompTIA DataSys+ objectives, choosing the appropriate data type is a fundamental database design decision that directly affects storage efficiency, performance, and data integrity. Product quantities represent whole numbers, such as the count of items in inventory, units sold, or stock remaining. Because these values do not require decimal precision, an integer-based data type is the most appropriate and storage-efficient choice.
An INTEGER data type is specifically designed to store whole numbers and consumes significantly less storage than floating-point or double-precision data types. DataSys+ emphasizes that database administrators should always select the smallest data type that accurately represents the data, as this reduces disk usage, improves cache efficiency, and enhances query performance-especially in large tables with millions of rows.
Option A, DOUBLE, and option D, FLOAT, are floating-point data types intended for values that require decimal precision, such as scientific measurements or financial calculations involving fractions. These data types consume more storage and can introduce rounding errors, making them unsuitable for storing simple quantity counts. Using floating-point types for inventory quantities would be inefficient and unnecessary.
Option C, COUNT, is not a data type at all. COUNT is an aggregate SQL function used in queries to calculate the number of rows or non-null values in a result set. It cannot be used to define a column in a table schema.
CompTIA DataSys+ highlights that efficient schema design includes proper data typing to minimize resource consumption while maintaining accuracy. By using INTEGER for product quantities, administrators ensure optimal storage utilization, faster indexing, and predictable arithmetic operations.
Therefore, to store product quantities accurately while consuming the minimal amount of storage, INTEGER is the best and most appropriate choice, making option B the correct and fully verified answer.
NEW QUESTION # 94
(Which of the following should a database administrator monitor to ensure a database has enough physical storage available to maintain performance expectations? Select two.)
Answer: D,F
Explanation:
The correct answers are B. Disk space and D. Database size growth. CompTIA DataSys+ places strong emphasis on storage monitoring as a critical responsibility of a database administrator (DBA), particularly to ensure ongoing performance, availability, and capacity planning. Physical storage constraints directly affect database operations such as inserts, updates, indexing, backups, and transaction logging.
Disk space monitoring is essential because databases require sufficient free storage not only for data files, but also for transaction logs, temporary files, indexes, and maintenance operations. If disk space becomes constrained, the database may experience degraded performance, failed write operations, or complete service outages. DataSys+ highlights proactive disk monitoring as a best practice to prevent unplanned downtime and emergency remediation.
Database size growth is equally important because it enables the DBA to anticipate future storage needs.
Databases rarely remain static; they grow as new records are added, indexes expand, and historical data accumulates. By tracking growth trends, administrators can forecast when additional storage will be required and take action before performance is impacted. DataSys+ identifies capacity planning as a key operational task, and monitoring growth patterns is central to that process.
Option A, network traffic, affects connectivity and throughput but does not determine physical storage availability. Option C, concurrent connections, relates to workload and performance but not disk capacity.
Option E, CPU usage, and option F, RAM usage, are critical server health metrics, but they do not indicate whether sufficient physical storage exists.
CompTIA DataSys+ clearly distinguishes between compute resources and storage resources. To ensure adequate physical storage and sustained performance, DBAs must monitor both current disk utilization and long-term database growth. Therefore, B and D are the correct and fully verified answers.
NEW QUESTION # 95
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