試験の準備方法-高品質なSDS試験勉強過去問試験-ユニークなSDS試験対策書JapancertはSDS認定試験に対する短期で有効な訓練を提供するウェブサイト、SDS認定試験が生活の変化をもたらすテストでございます。合格書を持ち方が持たない人により高い給料をもうけられます。 DASCA Senior Data Scientist 認定 SDS 試験問題 (Q29-Q34):質問 # 29
Spark programs can be written in:
A. Python
B. Scala
C. None of the above
D. All of the above
E. Java
正解：D
解説：
Apache Spark supports multiple programming languages for developing distributed applications:
Java (Option A): Supported through Spark's JVM-based APIs.
Scala (Option B): Spark is natively written in Scala, and Scala APIs provide full functionality.
Python (Option C): Supported via PySpark, enabling Python developers to leverage Spark.
Additionally, Spark also supports R and SQL-like queries, making it versatile for data scientists and engineers.
Thus, the correct answer is Option D (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming Tools: Spark APIs for Java, Scala, Python, and R.
質問 # 30
Which of the following is NOT an example of the applications of neural networks?
A. Character recognition
B. Stock market prediction
C. Traveling salesman's problem
D. None of the above
E. Image compression
正解：C
解説：
Neural networks have been widely applied in various domains:
Option A (Character recognition): Correct application - neural networks are highly effective for OCR (Optical Character Recognition).
Option B (Stock market prediction): Correct application - neural networks are used to model time-series and nonlinear patterns in finance.
Option D (Image compression): Correct application - neural nets (autoencoders) are used for dimensionality reduction and compression.
Option C (Traveling salesman's problem): NOT a typical neural network application. This is a combinatorial optimization problem usually solved with heuristics, dynamic programming, or optimization algorithms (not standard neural networks).
Thus, the correct answer is Option C (Traveling salesman's problem).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Machine Learning Applications of Neural Networks.
質問 # 31
Which of the following is correct about microservices?
A. Each service can be developed in any language that best fits the requirement
B. Each service is independent
C. All of the above
D. Each service is a new project
正解：C
解説：
Microservices architecture is a software design approach where applications are developed as a collection of small, loosely coupled, and independently deployable services.
Option A: Correct. Each microservice runs independently and has its own lifecycle, allowing scalability and modularity.
Option B: Correct. Each service can be treated as an independent project with its own repository, build pipeline, and deployment.
Option C: Correct. Microservices can be developed in different programming languages or frameworks, chosen based on the best fit for each specific requirement.
Therefore, the correct answer is Option D (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Data Management & Engineering: Microservices in Data Ecosystems.
質問 # 32
Which of the following is a useful feature of functional programming?
A. Lazy Evaluation
B. Higher-Order Functions (HOFs)
C. Immutable Data
D. All of the above
正解：D
解説：
Functional programming (FP) is a paradigm widely adopted in data science and big data tools (e.g., Spark with Scala/Python). Its useful features include:
Option A (Higher-Order Functions): Functions can take other functions as arguments or return them, enabling powerful abstractions like map(), reduce(), and filter().
Option B (Immutable Data): Ensures reliability and thread-safety, crucial for distributed computing. Once created, data structures cannot be modified, preventing side effects.
Option C (Lazy Evaluation): Computations are delayed until results are needed, improving performance in large-scale data operations.
Since FP leverages all three features, the correct answer is Option D (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming for Data Science: Functional Programming in Data Science Tools.
質問 # 33
Which of the following is NOT used to implement Agile?
A. Kanban
B. Extreme Programming (XP)
C. Six Sigma
D. Scrum
正解：C
解説：
Agile is a project management and product development methodology that emphasizes flexibility, iterative development, collaboration, and adaptability. Common frameworks that implement Agile principles include:
Scrum (Option A): A widely used Agile framework where work is divided into time-boxed sprints, roles are clearly defined (Scrum Master, Product Owner, Development Team), and progress is tracked via tools like burn down charts.
Kanban (Option B): A visual Agile method that manages workflow using a pull-based system with Kanban boards to visualize tasks and control work in progress (WIP).
Extreme Programming (XP, Option D): Another Agile method that focuses on high-quality software through technical practices like continuous integration, test-driven development (TDD), and pair programming.
By contrast:
Six Sigma (Option C): Six Sigma is a process improvement methodology that emphasizes reducing defects and improving quality through statistical analysis. It is not considered an Agile implementation framework.
Thus, the correct answer is Six Sigma (C).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Agile Methodologies and Project Management in Data Science.