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Oracle Senior Data Analyst Interview Questions and Answers

Updated 26 Jun 2024

Oracle Senior Data Analyst Interview Experiences

1 interview found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
6-8 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed before Jun 2023. There were 2 interview rounds.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Why are you changing the company
  • Q2. What are the skills you are looking for
Round 2 - Technical 

(2 Questions)

  • Q1. What is distinct in SQL?
  • Ans. 

    DISTINCT is used in SQL to retrieve unique values from a column or set of columns.

    • DISTINCT eliminates duplicate rows from the result set

    • It is often used in SELECT statements to only return unique values

    • Example: SELECT DISTINCT column_name FROM table_name

  • Answered by AI
  • Q2. What are joins in SQL
  • Ans. 

    Joins in SQL are used to combine rows from two or more tables based on a related column between them.

    • Joins are used to retrieve data from multiple tables based on a related column

    • Common types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN

    • Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column

  • Answered by AI

Skills evaluated in this interview

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
Hard
Process Duration
Less than 2 weeks
Result
No response

I applied via Recruitment Consulltant and was interviewed in Oct 2024. There was 1 interview round.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Question about Googlyness
  • Q2. Question about Google Lens, a RCA question

Interview Preparation Tips

Topics to prepare for Google Senior Data Analyst interview:
  • Root Cause Analysis
  • Guesstimates
  • Leadership
Interview preparation tips for other job seekers - Research about Google's core values and principles.

Learn how to do a RCA and a Guesstimate.

Learn how to answer in STAR method.
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Company Website and was interviewed in Dec 2024. There were 3 interview rounds.

Round 1 - Assignment 

Basic self evaluation test.

Round 2 - Technical 

(3 Questions)

  • Q1. What project I have completed and follow-up questions on that?
  • Q2. How to handle class imbalance.
  • Ans. 

    Handling class imbalance involves techniques like resampling, using different algorithms, and adjusting class weights.

    • Use resampling techniques like oversampling or undersampling to balance the classes.

    • Utilize algorithms that are robust to class imbalance, such as Random Forest, XGBoost, or SVM.

    • Adjust class weights in the model to give more importance to minority class.

    • Use evaluation metrics like F1 score, precision, r...

  • Answered by AI
  • Q3. Basic Python coding questions.
Round 3 - Technical 

(2 Questions)

  • Q1. Data-related questions.
  • Q2. ML Ops questions.

Interview Preparation Tips

Topics to prepare for Amdocs Data Scientist interview:
  • Python
  • MLOPS
Interview preparation tips for other job seekers - Prepare your projects well. And be ready for basic python coding questions. Prepare MlOps roles as well.
Interview experience
1
Bad
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
No response

I applied via Company Website and was interviewed in Jul 2024. There was 1 interview round.

Round 1 - Technical 

(6 Questions)

  • Q1. Asked Algorithms used in the project (No follow-up on mentioned algorithms, cut-off mid-explanation of business problem, scale, and solution wanting to know just the names of the algorithm) - Answered by n...
  • Q2. Count all pairs of numbers from a list where the ending digit of the ith number equals the starting digit of the jth number. Example [122, 21, 21, 23] should have 5 pairs (122, 21), (122, 21), (122, 23), (...
  • Ans. 

    Count pairs of numbers where ending digit of ith number equals starting digit of jth number.

    • Iterate through each pair of numbers in the list

    • Check if the ending digit of the ith number equals the starting digit of the jth number

    • Increment the count if the condition is met

  • Answered by AI
  • Q3. Interpretation of graphs, the first graph had perpendicular lines from the error to the fitted line and the second graph had lines from the error to the fitted line, parallel to the y-axis. - Interpreted t...
  • Ans. 

    Interpretation of graphs in linear regression analysis

    • Perpendicular lines from error to fitted line in first graph indicate OLS using projection matrices

    • Lines parallel to y-axis from error to fitted line in second graph suggest evaluation of linear regression to y-pred - y-actual method

    • PCA could also be a possible interpretation for the second graph

  • Answered by AI
  • Q4. What does np.einsum() do
  • Ans. 

    np.einsum() performs Einstein summation on arrays.

    • Performs summation over specified indices

    • Can also perform other operations like multiplication, contraction, etc.

    • Syntax: np.einsum(subscripts, *operands)

  • Answered by AI
  • Q5. How to generate random numbers using numpy, what is the difference between numpy.random.rand and numpy.random.randn
  • Ans. 

    numpy.random.rand generates random numbers from a uniform distribution, while numpy.random.randn generates random numbers from a standard normal distribution.

    • numpy.random.rand generates random numbers from a uniform distribution between 0 and 1.

    • numpy.random.randn generates random numbers from a standard normal distribution with mean 0 and standard deviation 1.

    • Example: np.random.rand(3, 2) will generate a 3x2 array of r...

  • Answered by AI
  • Q6. Difference between logit and probabilities in deep learning
  • Ans. 

    Logit is the log-odds of the probability, while probabilities are the actual probabilities of an event occurring.

    • Logit is the natural logarithm of the odds ratio, used in logistic regression.

    • Probabilities are the actual likelihood of an event occurring, ranging from 0 to 1.

    • In deep learning, logit values are transformed into probabilities using a softmax function.

    • Logit values can be negative or positive, while probabili

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - The interview seems to be designed for freshers, so brush up on libraries, and the functions inside them (utilization not the working).
No mathematics/statistics/probability/algorithm is discussed in terms of implementations, or enhancements.

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

It is nice to do work

Round 2 - Aptitude Test 

It helps in understanding the 5

Round 3 - Coding Test 

It helps a lot in company

Round 4 - Technical 

(5 Questions)

  • Q1. How to do job in company?
  • Q2. What I should do?
  • Q3. How to do work?
  • Q4. What should I do
  • Q5. What is the goal?
  • Ans. 

    The goal of a Data Analyst is to analyze data to extract valuable insights and make data-driven decisions.

    • Identify trends and patterns in data

    • Create visualizations to communicate findings

    • Provide actionable recommendations based on data analysis

  • Answered by AI
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Feb 2024. There were 5 interview rounds.

Round 1 - HR 

(2 Questions)

  • Q1. Self-introduction
  • Q2. What are your roles and responsibilities in current organization
  • Ans. 

    I am responsible for analyzing data, creating reports, and providing insights to support decision-making.

    • Analyze large datasets to identify trends and patterns

    • Create reports and dashboards to visualize data for stakeholders

    • Provide insights and recommendations based on data analysis

    • Collaborate with cross-functional teams to drive data-driven decision-making

  • Answered by AI
Round 2 - One-on-one 

(2 Questions)

  • Q1. Self-introduction
  • Q2. Brief discussion about the roles and responsibilities for current opening
  • Ans. 

    Lead Data Analyst oversees data analysis team, develops strategies, interprets data, and presents insights to stakeholders.

    • Manage and lead a team of data analysts

    • Develop data analysis strategies and methodologies

    • Interpret data and provide actionable insights to stakeholders

    • Collaborate with cross-functional teams to drive data-driven decision making

    • Ensure data quality and accuracy in analysis

    • Stay updated on industry tre

  • Answered by AI
Round 3 - Technical 

(3 Questions)

  • Q1. Self-introduction
  • Q2. Technical round for Python, SQL, Tableau and Advanced Excel
  • Q3. Scenario based questions
Round 4 - One-on-one 

(3 Questions)

  • Q1. Self-Introduction
  • Q2. What do you understand about Sales Comp and its roles and responsibilities
  • Ans. 

    Sales Comp is a system that determines how salespeople are compensated based on their performance.

    • Sales Comp is short for Sales Compensation

    • It involves designing and implementing a system to reward salespeople based on their sales performance

    • Roles include setting sales targets, determining commission structures, and monitoring sales performance

    • Responsibilities include analyzing sales data, calculating commissions, and ...

  • Answered by AI
  • Q3. Scenario based questions
Round 5 - One-on-one 

(2 Questions)

  • Q1. Self-introduction
  • Q2. Scenario based questions

Interview Preparation Tips

Topics to prepare for Salesforce Lead Data Analyst interview:
  • Sales comp
  • Data Analysis
  • Python
  • SQL
  • Tableau
  • Advanced Excel
  • CRM
Interview preparation tips for other job seekers - Before going to interview, first thoroughly read about the roles and responsibilities. Make yourself prepared accordingly.

Ask questions to the interviewer to understand their expectations for the role you are applying for.

Do some research about the company and the pay scale for your roles and put your expectations accordingly.
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Referral and was interviewed in Mar 2024. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Basic of python , sql, pandas,niumpy
Round 2 - Technical 

(1 Question)

  • Q1. Gave me a task to make web app for medical condition detection after clearing first round asked questions relted to it

Data Scientist Interview Questions & Answers

Chetu user image Abhilasha Dimble

posted on 22 Feb 2024

Interview experience
1
Bad
Difficulty level
Hard
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Jan 2024. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. Asked about projects. What is classification? Is knn used for regression?how? decision tree working for regression and classification Is naive Bayes used for regression?how? LLM Docker Aws GenAI Code for ...

Interview Preparation Tips

Interview preparation tips for other job seekers - Guys, interviewer is really wierd...very rude...
Starts interview with lots of questions..
He interrupts me in every question's answer.. doesn't even ready listen my answers ...
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via LinkedIn and was interviewed in Dec 2023. There was 1 interview round.

Round 1 - Coding Test 

Find the Highest profit by geo

Interview Preparation Tips

Interview preparation tips for other job seekers - Study data
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Dec 2022. There were 3 interview rounds.

Round 1 - Coding Test 

String Reverse Coding Test


User
Share Detail for coding test

ChatGPT
Certainly! I'd be happy to provide you with details for a coding test. Here's an example of a coding test description:

Title: String Reversal

Description:
Write a function that takes a string as input and returns the reverse of that string. The function should reverse the order of characters in the string and return the reversed string as the output.

Requirements:

The function should be named reverseString and take a single parameter, inputString, of type string.
The function should return a string.
The function should handle both uppercase and lowercase letters.
The function should preserve any whitespace or special characters in the input string.
The function should not use any built-in or library functions that directly solve this problem.
Example:
Input: "Hello, World!"
Output: "!dlroW ,olleH"

Note:

The input string can be of any length.
The input string may contain alphanumeric characters, whitespace, or special characters.
Evaluation Criteria:

Correctness of the solution.
Efficiency and clarity of the code.
Proper handling of edge cases and error conditions.
Adherence to coding best practices.
Please complete the task within 30 minutes and submit your solution as a single file. Feel free to use any programming language you are comfortable with.
Good luck!

Round 2 - Aptitude Test 

String Reverse Coding Test


User
Share Detail for coding test

ChatGPT
Certainly! I'd be happy to provide you with details for a coding test. Here's an example of a coding test description:

Title: String Reversal

Description:
Write a function that takes a string as input and returns the reverse of that string. The function should reverse the order of characters in the string and return the reversed string as the output.

Requirements:

The function should be named reverseString and take a single parameter, inputString, of type string.
The function should return a string.
The function should handle both uppercase and lowercase letters.
The function should preserve any whitespace or special characters in the input string.
The function should not use any built-in or library functions that directly solve this problem.
Example:
Input: "Hello, World!"
Output: "!dlroW ,olleH"

Note:

The input string can be of any length.
The input string may contain alphanumeric characters, whitespace, or special characters.
Evaluation Criteria:

Correctness of the solution.
Efficiency and clarity of the code.
Proper handling of edge cases and error conditions.
Adherence to coding best practices.
Please complete the task within 30 minutes and submit your solution as a single file. Feel free to use any programming language you are comfortable with. Good luck!





User
Share derail for amplitude test

ChatGPT
Certainly! Here's an example of a coding test description for an amplitude test:

Title: Finding Amplitude

Description:
Write a function that takes a list of integers as input and returns the amplitude of the list. The amplitude of a list is defined as the difference between the largest and smallest elements in the list.

Requirements:

The function should be named findAmplitude and take a single parameter, inputList, which is a list of integers.
The function should return an integer representing the amplitude of the input list.
The function should handle both positive and negative integers.
The function should handle an empty list as input and return 0 as the amplitude.
Example:
Input: [2, 5, 9, -1, 3, 7]
Output: 10

Explanation:
The largest element in the list is 9, and the smallest element is -1. Therefore, the amplitude is 9 - (-1) = 10.

Note:

The input list can contain duplicates.
The input list can be of any length.
Evaluation Criteria:

Correctness of the solution.
Efficiency and clarity of the code.
Proper handling of edge cases and error conditions.
Adherence to coding best practices.
Please complete the task within 30 minutes and submit your solution as a single file. Feel free to use any programming language you are comfortable with.
Good luck!

Round 3 - Group Discussion 

Certainly! Here's an example of a group discussion topic:

Topic: The Impact of Artificial Intelligence on the Job Market

Description:
In this group discussion, we will explore the impact of artificial intelligence (AI) on the job market. AI is rapidly advancing, and its integration into various industries and sectors has raised concerns about the future of work.

Points to consider:
Potential job displacement: Discuss how AI has the potential to automate tasks and replace human jobs in various fields. Explore which industries or job roles are most susceptible to automation and the potential consequences for workers.

Job creation: Explore the other side of the argument and discuss how AI can also create new job opportunities. Consider the emergence of AI-related roles such as data scientists, AI trainers, and AI ethicists. Discuss the skills and expertise required for these new job roles.

Skills and education: Discuss the importance of skills development and education in adapting to the changing job market. Explore what skills will be in high demand in an AI-driven economy and how individuals and organizations can upskill or reskill to remain relevant.

Ethical considerations: Consider the ethical implications of AI in the job market. Discuss issues such as algorithmic bias, data privacy, and the responsibility of companies and policymakers in ensuring a fair and inclusive job market.

Job market transformation: Discuss the overall transformation of the job market due to AI. Explore how AI is reshaping traditional job roles, the gig economy, and the potential for new forms of work, such as remote work and flexible arrangements.

Guidelines:

Each participant should express their thoughts and ideas clearly and respectfully.
Encourage active listening and give everyone an opportunity to speak.
Support your arguments with relevant examples or data, if possible.
Be open to different perspectives and engage in constructive debate.
Evaluation Criteria:

Clarity of thought and expression.
Ability to articulate and support arguments.
Active participation and engagement with other participants.
Respectful and collaborative attitude towards the group discussion.
Please prepare your thoughts on the topic before the discussion. The group discussion will last for approximately 30 minutes. Good luck!

Interview Preparation Tips

Interview preparation tips for other job seekers - As a data science job seeker, here are some key pieces of advice to help you in your job search:

Develop a Strong Foundation: Ensure you have a solid understanding of the fundamental concepts and techniques in data science. This includes knowledge of statistics, mathematics, programming (Python and R are commonly used), machine learning algorithms, and data manipulation.

Build a Portfolio: Create a portfolio that showcases your data science skills and projects. This could include personal projects, Kaggle competition entries, or contributions to open-source projects. A portfolio demonstrates your practical experience and can set you apart from other candidates.

Gain Practical Experience: Seek out opportunities to work on real-world data science problems. Consider internships, freelance projects, or collaborations with researchers or companies. Practical experience not only enhances your skills but also demonstrates your ability to apply your knowledge to solve real problems.

Stay Updated: Keep up with the latest developments in the field of data science. Follow blogs, participate in online forums and communities, and attend conferences or webinars. Being aware of emerging technologies, techniques, and trends shows your dedication to continuous learning and growth.

Network: Build connections within the data science community. Attend industry events, join professional organizations, and engage with professionals through social media platforms like LinkedIn and Twitter. Networking can lead to valuable job opportunities, referrals, and insights into the industry.

Customize Your Applications: Tailor your resume and cover letter for each job application. Highlight relevant skills, projects, and experiences that align with the specific requirements of the position. A personalized application shows your attention to detail and genuine interest in the role.

Prepare for Interviews: Be prepared for technical interviews that assess your data science skills. Practice coding exercises, algorithmic problem-solving, and be able to explain your projects in a clear and concise manner. Additionally, be prepared to answer behavioral and situational questions to demonstrate your problem-solving, teamwork, and communication skills.

Continuously Learn and Improve: Data science is a rapidly evolving field, so embrace a growth mindset. Seek opportunities to learn new techniques, explore new domains, and expand your skill set. Take online courses, attend workshops, or pursue advanced degrees if necessary. Show that you are committed to staying ahead of the curve.

Emphasize Communication Skills: Data scientists are not just expected to analyze data but also effectively communicate their findings to non-technical stakeholders. Develop your ability to present complex concepts in a clear and concise manner, both verbally and in written form. Strong communication skills will make you a valuable asset to any organization.

Be Persistent and Resilient: The job search process can be challenging and may require time and perseverance. Don't get discouraged by rejection or setbacks. Learn from each experience, seek feedback, and continuously refine your approach. With persistence and a positive attitude, you'll increase your chances of landing a data science job.

Remember, the field of data science is highly competitive, so it's important to stand out from the crowd. By following these tips and continuously improving your skills, you can increase your chances of securing a rewarding job in data science. Good luck with your job search!

Oracle Interview FAQs

How many rounds are there in Oracle Senior Data Analyst interview?
Oracle interview process usually has 2 rounds. The most common rounds in the Oracle interview process are One-on-one Round and Technical.
How to prepare for Oracle Senior Data Analyst interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Oracle. The most common topics and skills that interviewers at Oracle expect are Data Analytics, Data Interpretation, Excel and Statistics.
What are the top questions asked in Oracle Senior Data Analyst interview?

Some of the top questions asked at the Oracle Senior Data Analyst interview -

  1. What is distinct in S...read more
  2. What are joins in ...read more

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Oracle Senior Data Analyst Interview Process

based on 2 interviews

Interview experience

4.5
  
Good
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Senior Data Analyst Interview Questions from Similar Companies

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Oracle Senior Data Analyst Salary
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₹4 L/yr - ₹13.5 L/yr
20% less than the average Senior Data Analyst Salary in India
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based on 2 reviews

3.3/5

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3.6

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4.3

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2.6

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Job security

2.9

Company culture

1.9

Promotions

2.9

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