Dimension India Network Interview Questions and Answers

A question that is both tricky and simple.

Q1. Questions about biochemistry
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Questions based on both numerical data and case studies.

Q1. Can you tell me about yourself?
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Q2. What interests you in working for this company?
Ans. 
I am interested in working for this company because of its innovative projects and strong reputation in the industry.
• Innovative projects that challenge me to grow as a programmer

• Strong reputation in the industry for quality work

• Opportunities for career advancement and professional development
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Q1. All employees having same salary in the smae department sql and pysprk
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Q2. How to create pipeline in databricks
Ans. 
To create a pipeline in Databricks, you can use Databricks Jobs or Apache Airflow for orchestration.
• Use Databricks Jobs to create a pipeline by scheduling notebooks or Spark jobs.

• Utilize Apache Airflow for more complex pipeline orchestration with dependencies and monitoring.

• Leverage Databricks Delta for managing data pipelines with ACID transactions and versioning.
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Q3. Palindrome, 2nd char in every word make is to upper case, sql rank and dense rank releated questions , given 2 tables country and city we need to calculate total population in each continent by joining the...read more
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Q4. String manuplation questions inpython
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Q1. What is an abstract class?
Ans. 
An abstract class is a class that cannot be instantiated and may contain abstract methods that must be implemented by its subclasses.
• Cannot be instantiated directly

• May contain abstract methods

• Used as a blueprint for other classes
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Q2. What is abstraction?
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Abstraction is the process of hiding complex details and showing only the essential features of an object or system.
• Abstraction allows us to focus on what an object does, rather than how it does it

• It helps in simplifying complex systems by breaking them down into smaller, more manageable parts

• Examples of abstraction include using a car without needing to understand its internal combustion engine, or using a smartphone
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Q3. Best sorting algo?time complexity of it?
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QuickSort is one of the best sorting algorithms with an average time complexity of O(n log n).
• QuickSort is a divide and conquer algorithm that works by selecting a 'pivot' element and partitioning the array around the pivot.

• It has an average time complexity of O(n log n) and a worst-case time complexity of O(n^2).

• Example: ['apple', 'banana', 'cherry', 'date', 'fig'] can be sorted using QuickSort.

• Example: ['3', '1', '4'...read more
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Q4. You have been provided a sorted list time complexity achieved after we apply bubble sorting
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Bubble sorting has a time complexity of O(n^2) for a sorted list.
• Bubble sorting has a worst-case time complexity of O(n^2) for a sorted list.

• The time complexity does not change even if the list is already sorted.

• Example: If we have a sorted list of size n, bubble sorting will still take O(n^2) time.
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Q1. Have you ever been to a state other than jharkhand?
Ans. 
Yes, I have been to multiple states other than Jharkhand.
• I have traveled to states like Maharashtra, Karnataka, and Tamil Nadu for work and leisure.

• I have visited tourist destinations in states like Rajasthan, Kerala, and Himachal Pradesh.

• I have family in states like Uttar Pradesh, Bihar, and West Bengal, which I have visited multiple times.
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Q1. What is the Java code for reversing a linked list?
Ans. 
Reversing a linked list in Java using iterative approach.
• Create three pointers: prev, current, and next.

• Iterate through the list, updating pointers to reverse the links.

• Return the new head of the reversed list.
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Q2. How do you handle the StaleElementReferenceException in your code?
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Handle StaleElementReferenceException by re-locating the element before interacting with it.
• Use try-catch block to catch StaleElementReferenceException

• Re-locate the element using findElement method before interacting with it

• Use WebDriverWait to wait for the element to become stale
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Q1. Can you describe your project experiences?
Ans. 
I have worked on various projects involving test automation, performance testing, and quality assurance processes.
• Developed automated test scripts using Selenium WebDriver for web applications

• Conducted performance testing using JMeter to identify bottlenecks and optimize system performance

• Implemented quality assurance processes to ensure software meets requirements and standards

• Collaborated with cross-functional teams ...read more
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Q2. What is your strategy for designing an automation framework?
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My strategy for designing an automation framework involves identifying key functionalities, selecting appropriate tools, creating reusable components, implementing robust error handling, and integrating with CI/CD pipelines.
• Identify key functionalities to be automated based on priority and impact on testing.

• Select appropriate tools and technologies based on the application under test and team expertise.

• Create reusable ...read more
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Q1. Coalesce, SQL Order of Execution
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Q2. Given a table with fields(id, name, salary, managerId) find out the managers who have atleast 5 reportees under him/her.
Ans. 
Use SQL query to count number of reportees for each manager and filter out those with atleast 5 reportees.
• Write a SQL query to count number of reportees for each manager using GROUP BY clause

• Add HAVING clause to filter out managers with atleast 5 reportees

• Example: SELECT managerId, COUNT(id) AS num_reportees FROM table_name GROUP BY managerId HAVING num_reportees >= 5
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Q3. How to manage large datasets in python
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Use libraries like pandas and dask to efficiently manage large datasets in Python.
• Use pandas library for data manipulation and analysis.

• Use dask library for parallel computing and out-of-core processing.

• Optimize memory usage by loading data in chunks or using data types efficiently.

• Consider using cloud services like AWS S3 or Google BigQuery for storing and processing large datasets.
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Q4. Name few of the commonly used python libraries used by DA
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Some commonly used Python libraries for Data Analysts are Pandas, NumPy, Matplotlib, and Scikit-learn.
• Pandas - used for data manipulation and analysis

• NumPy - used for numerical computing and working with arrays

• Matplotlib - used for data visualization

• Scikit-learn - used for machine learning and data mining
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