Dell D-DS-FN-23 Practice Exam Questions & Answers
7 Free Questions
· Last reviewed: October 15, 2026
· Prepared & Reviewed by the ValidExamDumps Editorial Team
Exam Facts
Dell D-DS-FN-23 Exam Details
Key details for this exam, checked against the published exam outline
59
Practice Questions (Our Bank)
90 minutes
Exam Duration
60%
Passing Score
USD 230
Official Exam Fee
- Exam Code
- D-DS-FN-23
- Full Name
- Dell Certified Data Science Foundations
- Issuing Body
- Dell EMC
- Question Format (Our Bank)
- Multiple Choice, Drag & Drop
- Delivery
- Pearson VUE
Practice Questions
Free D-DS-FN-23 Practice Questions
Each question shows the correct answer and an explanation of why it is right
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preparation team, who also write the explanation shown with each one.
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Question 1
On which type of data should you run K-means clustering?
Correct Answer:
B
Question 2
What is a business driver for Big Data analytics adoption?
Correct Answer:
C
Question 3
MapReduce is designed to process data in which way?
Correct Answer:
A
Question 4
In time series analysis, what function is examined to identify the order of the autoregressive component of an ARIMA model?
Correct Answer:
C
Question 5
Executives want to determine whether a change in a shopping rewards program has been effective in getting customers to increase their spending. Which approach could be used to determine if a significant shift in spending has occurred?
Correct Answer:
A
Question 6
In which programming language is Hadoop written?
Correct Answer:
C
Question 7
What converts SQL-like commands into either Tez, Spark, or MapReduce jobs that are submitted to the Hadoop cluster?
Correct Answer:
C
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Domain 1: Big Data, Analytics, and the Data Scientist Role
5%
Candidates learn to define big data characteristics and understand the business drivers behind analytics adoption. This domain covers the core skills and responsibilities expected of data scientists in modern organisations.
Domain 2: Data Analytics Lifecycle
8%
The exam tests understanding of each phase from discovery through operationalisation, including the specific activities and roles within discovery, data preparation, model planning, and model building. Mastery here ensures candidates grasp the sequential nature of applied analytics work.
Domain 3: Initial Analysis of the Data
15%
Candidates must demonstrate proficiency with basic R commands for data exploration and explain key statistical measures and visualisations. Hypothesis testing theory and practical application of results evaluation are essential skills at this stage.
Domain 4: Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods
40%
This domain dominates the exam and requires deep understanding of k-means clustering, association rules, linear and logistic regression, naive Bayesian classifiers, decision trees, time series analysis, and text analytics. Candidates must not only know each method but interpret results correctly in business contexts.
Domain 5: Advanced Analytics for Big Data - Technology and Tools
22%
Coverage spans MapReduce and Apache Hadoop architecture, the broader Hadoop ecosystem with its use cases, in-database analytics, and SQL techniques including window functions, ordered aggregates, and MADlib. Understanding these tools prepares candidates for implementing analytics at scale.
Domain 6: Operationalizing an Analytics Project and Data Visualization Techniques
10%
Candidates learn best practices for presenting findings to different audiences and translating analytics into business action. Effective data visualisation and project communication are essential for moving analytics from experiment to production.
FAQ
D-DS-FN-23 Exam FAQ
Common questions about the exam itself
What job role does the D-DS-FN-23 prepare me for?
The certification validates foundational knowledge needed for entry-level and intermediate data science roles. It demonstrates to employers that you understand the analytics lifecycle, core statistical methods, and big data tools, positioning you for positions like Junior Data Scientist or Analytics Associate.
How difficult is D-DS-FN-23 compared to other data science certifications?
The exam sits between tool-heavy certifications and abstract theoretical qualifications, testing both maths and practical analytics methods without locking you into one vendor's ecosystem. The 40 percent weighting on advanced analytics methods makes this domain the primary difficulty driver.
What background do I need before taking D-DS-FN-23?
You should have basic understanding of statistics and programming, particularly Python and SQL. Hands-on experience running a regression or clustering analysis significantly boosts confidence with the interpretation-heavy questions covering the eight analytical methods.
Which domain of D-DS-FN-23 gives candidates the most trouble?
Advanced Analytics accounts for 40 percent of the exam and demands practical understanding of eight different methods and their real-world application. Candidates struggle most when they memorise methods without working through actual data analysis to build intuition for correct interpretation.
How long should I prepare for D-DS-FN-23?
Preparation time depends on your background, but plan for 6 to 12 weeks of study combining theoretical review with hands-on practice. Candidates with data analysis experience typically need the shorter timeframe, while those new to statistics and analytics require more time on the advanced methods domain.
What is the passing score for D-DS-FN-23 and how is it calculated?
You need to score 60 percent or higher to pass. The exam contains 60 multiple-choice questions, giving you roughly one and a half minutes per question, which is comfortable for recall but tight for the interpretation-heavy advanced analytics section.
Can I retake D-DS-FN-23 if I fail, and what are the rules?
Dell allows retakes, but you will need to purchase a new exam voucher for each attempt. Check with your exam delivery provider Pearson VUE for any waiting periods or policies on retake scheduling.
How long is the D-DS-FN-23 certification valid once I pass?
Dell EMC does not publish a specific validity period for this certification, meaning it does not expire. However, you should stay current with evolving data science practices and tools to keep your skills relevant.
What comes after D-DS-FN-23 in the Dell data science certification track?
The Data Science Foundations credential serves as a stepping stone toward advanced Dell certifications in data engineering, machine learning operations, and industry-specific analytics applications. These follow-on certifications let you deepen expertise in predictive modelling, natural language processing, or real-time analytics.
Where and how do I take the D-DS-FN-23 exam?
The exam is delivered through Pearson VUE, either online with remote proctoring or at a physical test centre. You have 90 minutes to complete 60 multiple-choice questions.
