SysCloud Interview Questions and Answers

Basic self evaluation test.

Q1. What project I have completed and follow-up questions on that?
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Q2. How to handle class imbalance.
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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...read more
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Q3. Basic Python coding questions.
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Q1. Data-related questions.
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Q2. ML Ops questions.
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Q1. What is ipconf.pl?
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Q2. What is the difference between scan vip & node vip?
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Q1. What is quarantile in Exadata?
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Q2. How to identify the master switch in Exadata?
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Q3. What is spine switch & leaf switch in exadata?
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One of the node of a 3 node cluster is down. Explain the step by step process to troubleshoot the issue.

Shell script & terraform code output was asked.

Q1. Introduction, roles and responsibilities
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Q2. Deep copy shallow copy
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Q3. Method Overloading overriding
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Q4. Constuctor and its types
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Q5. Varags (variable length arguments)
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Q6. Find element find elements return types of it if no elements found
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Q7. Webdriver what is it
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Q8. Find duplicate numbers and its count from given list explain logic
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Q9. Factorial using recursion
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Q1. Support Role Questions 1) Like explaining a case which was done in your previous role and experience
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Q2. Questions on Javascript
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Q1. Technical Interview questions on Javascript, HTML, CSS and behavioural
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Q1. Manager Questions based on Position and previous work experience.
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Basic Python, SQL, and Bash questions

Q1. SQL questions with operations that include changing from string to array. Tip: stick to RDBMS-specific dialects only (like Postgres), I used Spark SQL
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Q2. Simple Python questions with a follow-up to optimise it
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Q3. Bash script-based questions, are pretty basic.
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Q4. Data pipeline design and best practices.
Ans. 
Data pipeline design involves creating a system to efficiently collect, process, and analyze data.
• Understand the data sources and requirements before designing the pipeline.

• Use tools like Apache Kafka, Apache NiFi, or AWS Glue for data ingestion and processing.

• Implement data validation and error handling mechanisms to ensure data quality.

• Consider scalability and performance optimization while designing the pipeline.

• Doc...read more
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Q1. Easy to medium Leetcode-based question. With moderate difficulty.
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Q2. Simple Python-based question with optimisation.
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Q3. Design specific questions based on Data pipelines.
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Q1. SQL-based question with moderate difficulty.
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Q2. Python-based questions, follow questions with some optimisations.
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Q3. Bash-script based round.
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