Dell EMC D-DS-FN-23 Practice Exam Questions & Answers
5 Free Questions
· Last reviewed: September 10, 2026
· Prepared & Reviewed by the ValidExamDumps Editorial Team
Exam Facts
Dell EMC 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
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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What is a business driver for Big Data analytics adoption?
Correct Answer:
C
Explanation
The EXCEPT operator is a SQL set operator that returns rows from the first query that do not appear in the second query result set. This falls under Advanced Analytics for Big Data technology where SQL techniques are essential. Understanding set operators like EXCEPT, UNION, and INTERSECT is fundamental for working with large datasets. UNION would combine results, INTERSECT would return only matching rows, and JOIN is a different clause entirely. EXCEPT specifically handles the 'first but not second' scenario.
What is a benefit of Spark in-memory data processing as opposed to using MapReduce?
Correct Answer:
A
Explanation
Right-skewed data with a long tail can be transformed using logarithmic, square root, or power transformations to approximate normality. A logarithmic transformation compresses the larger values more than smaller ones, pulling in the right tail. Standardization and normalization only rescale data without changing its shape. Removing outliers is problematic as it discards information. Understanding data distributions and transformations belongs to initial data analysis where you assess your data characteristics before modeling.
Consider this SQL statement: SELECT product, avg(prod_cost) FROM product_detail GROUP BY product. The GROUP BY clause implies what type of function?
Correct Answer:
B
Explanation
Multinomial logistic regression extends binary logistic regression to handle dependent variables with three or more categories. Binary logistic regression works only for two-category outcomes, so when you have multiple categories you need the multinomial version. The number of independent variables and sample size are important but not the deciding factor. Data type considerations matter less than the actual target variable structure. This is core advanced analytics methodology.
In the data preparation phase of the data analytics lifecycle, what does the term ''data conditioning'' refer to?
Correct Answer:
D
Explanation
In a decision tree, a branch represents the outcome of a test or split on a variable at a node. Each branch leads to another node based on whether a condition is met. A leaf node is the terminal outcome. A root is the starting point. The trunk is not standard decision tree terminology. Branches show the decision paths the tree explores as it navigates through predictor variables to make predictions.
What action occurs during feature selection in the model building phase of the data analytics lifecycle?
Correct Answer:
C
Explanation
Project goals provide a succinct overview of the business situation and the reason the project exists. They explain what problem is being solved or what opportunity is being pursued. Background information is more detailed and historical. Methods describes how analysis was conducted. Recommendations presents solutions. In operationalizing analytics projects, clearly stating project goals early helps different audiences understand context and ensures alignment on objectives before diving into technical details.
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.
Sample question from this domain above:
Q2
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.
Sample questions from this domain above:
Q3Q4
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.
Sample question from this domain above:
Q1
Domain 6: Operationalising an Analytics Project and Data Visualisation 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.
Sample question from this domain above:
Q5
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.
