D-DS-FN-23 Dell Data Science Foundations 2023 Exam Dumps
July 27,2024
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D-DS-FN-23 Dell Data Science Foundations 2023
This qualifying exam for Data Science Foundations 2023 focuses on the practice of data analytics, the role of the Data Scientist, the main phases of the Data Analytics Lifecycle, analyzing and exploring data with R, statistics for model building and evaluation, the theory and methods of advanced analytics and statistical modeling, the technology and tools that can be used for advanced analytics, operationalizing an analytics project, and data visualization techniques. Successful candidates will achieve the Dell EMC Proven Professional – Data Science Associate credential. The exam has a duration of 90 minutes, consists of 60 questions, and requires a pass score of 60.
Exam Topics
Topics likely to be covered on this exam include:
Big Data, Analytics, and the Data Scientist Role (5%)
● Define and describe the characteristics of Big Data
● Describe the business drivers for Big Data analytics and data science
● Describe the Data Scientist role and related skills
Data Analytics Lifecycle (8%)
● Describe the data analytics lifecycle purpose and sequence of phases
● Discovery - Describe details of this phase, including activities and associated roles
● Data preparation - Describe details of this phase, including activities and associated roles
● Model planning - Describe details of this phase, including activities and associated roles
● Model building - Describe details of this phase, including activities and associated roles
Initial Analysis of the Data (15%)
● Explain how basic R commands are used to initially explore and analyze the data
● Describe and provide examples of the most important statistical measures and effective visualizations of data
● Describe the theory, process, and analysis of results for hypothesis testing and its use in evaluating a model
Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods (40%)
Describe theory, application, and interpretation of results for the following methods:
● K-means clustering
● Association rules
● Linear regression
● Logistic Regression
● Na?ve Bayesian classifiers
● Decision trees
● Time Series Analysis
● Text Analytics
Advanced Analytics for Big Data - Technology and Tools (22%)
● Describe the technological challenges posed by Big Data
● Describe the nature and use of MapReduce and Apache Hadoop
● Describe the Hadoop ecosystem and related product use cases
● Describe in-database analytics and SQL essentials
● Describe advanced SQL methods: window functions, ordered aggregates, and MADlib
Operationalizing an Analytics Project and Data Visualization Techniques (10%)
● Describe best practices for communicating findings and operationalizing an analytics project
● Describe best practices for building project presentations for specific audiences
● Describe best practices for planning and creating effective data visualizations
Share Dell Data Science Foundations D-DS-FN-23 Free Dumps
1. What is an appropriate assignment for a data scientist?
A. Monitor key performance indicators
B. Define an OLAP database schema
C. Conduct customer surveys
D. Develop predictive models
Answer: D
2. What is the output format from the Map function of MapReduce?
A. Key-value pairs
B. Binary representation of keys concatenated with structured data
C. Compressed index
D. Unique key record and separate records of all possible values
Answer: A
3. During the data preparation phase, you notice a high correlation between average spend on video games, age of players, and number of science fiction shows watched.
Which technique could you use to address the three correlated variables?
A. Square the three variables to remove the correlation
B. Combine the three variables into one new variable
C. Drop the three variables to improve the model
D. Use scaling to make the three variables equivalent in size
Answer: B
4. What are considerations in a data science and Big Data analytics project?
A. Ignoring executive stakeholders and business users
B. Applying the latest technologies to demonstrate technical skills
C. Analysis flexibility and decision making
D. Building data silos and bypassing data privacy rules
Answer: C
5. What is the primary function of the NameNode in Hadoop?
A. Keeps track of which MapReduce jobs have been assigned to each TaskTracker
B. Monitors the state of each JobTracker node and signals an event if unavailable
C. Runs some number of mapping tasks against its assigned data
D. Acts as a regulator/resolver among clients and DataNodes
Answer: D
6. What activities occur during the discovery phase of the data analytics lifecycle?
A. Deploy and monitor model performance
B. Build training and test datasets
C. Interview project sponsor and stakeholders
D. Perform ETL and data exploration
Answer: C
7. What is a motivation for using a data analytics lifecycle?
A. Explores all possible approaches
B. Limits the amount of data needed
C. Guarantees a successful project
D. Creates a repeatable process
Answer: D
8. What is a key consideration when preparing a presentation intended for sponsors?
A. Describe how current processes may be affected
B. Provide details on model planning and building
C. Describe how to implement the model
D. Emphasize the business benefits of implementing the model
Answer: D
9. Which characteristic applies only to Business Intelligence as opposed to Data Science?
A. Uses only structured data
B. Supports solving “what if” scenarios
C. Uses large data sets
D. Uses predictive modeling techniques
Answer: A
10. In which phase of the data analytics lifecycle do Data Scientists spend the most time in a project?
A. Discovery
B. Data Preparation
C. Model Building
D. Communicate Results
Answer: B
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