Carelon Global Solutions Data Management Associate Interview Questions and Answers

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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It is nice to do work

It helps in understanding the 5

It helps a lot in company

Q1. How to do job in company?
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Q2. What I should do?
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Q3. How to do work?
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Q4. What should I do
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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
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Q1. What is bigadata
Ans. 
Big data refers to large and complex data sets that are difficult to process using traditional data processing applications.
• Big data involves large volumes of data

• It includes data from various sources such as social media, sensors, and business transactions

• Big data requires specialized tools and technologies for processing and analysis
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Q2. How spark works
Ans. 
Spark is a distributed computing framework that processes big data in memory and is known for its speed and ease of use.
• Spark is a distributed computing framework that can process data in memory for faster processing.

• It uses Resilient Distributed Datasets (RDDs) for fault-tolerant distributed data processing.

• Spark provides high-level APIs in Java, Scala, Python, and R for ease of use.

• It supports various data sources li...read more
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Q3. Explain your application
Ans. 
Our application is a data engineering platform that processes and analyzes large volumes of data to provide valuable insights.
• Our application uses various data processing techniques such as ETL (Extract, Transform, Load) to clean and transform raw data into usable formats.

• We utilize big data technologies like Hadoop, Spark, and Kafka to handle large datasets efficiently.

• The application also includes machine learning al...read more
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Q1. Basic of python , sql, pandas,niumpy
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Q1. Gave me a task to make web app for medical condition detection after clearing first round asked questions relted to it
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Q1. Explain surrogate key
Ans. 
Surrogate key is a unique identifier used in databases to uniquely identify each record in a table.
• Surrogate keys are typically generated by the system and have no business meaning.

• They are used to simplify database operations and improve performance.

• Example: Using an auto-incrementing integer column as a surrogate key in a table.
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It's seems to be easy

It is quite difficult

Q1. How do you resolve gap on a Physical Standby in Dataguard ?
Ans. 
Resolve gap on a Physical Standby in Dataguard by identifying the missing archived redo log files and manually copying them over.
• Check the alert log for errors related to missing archived redo log files

• Identify the sequence number of the missing redo log files

• Manually copy the missing archived redo log files from the primary database to the standby database location

• Register the missing redo log files using the ALTER DA
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Q2. What do you do when client complains about poor performance of Database ?
Ans. 
Investigate the issue, analyze performance metrics, identify bottlenecks, optimize queries, and implement performance tuning.
• Investigate the issue by analyzing logs, monitoring tools, and gathering information from the client.

• Analyze performance metrics such as CPU usage, memory usage, disk I/O, and query execution times.

• Identify bottlenecks in the database system such as slow queries, inefficient indexing, or hardware...read more
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Q1. Do you have knowldge on cloud ?
Ans. 
Yes, I have knowledge on cloud computing.
• I have experience working with cloud databases like Oracle Cloud Database

• I am familiar with cloud storage solutions like Amazon S3 and Google Cloud Storage

• I have implemented cloud backup and disaster recovery strategies in previous roles
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Q2. Do you have knowledge on other RDBMS ?
Ans. 
Yes, I have knowledge on other RDBMS such as MySQL, SQL Server, and PostgreSQL.
• I have experience working with MySQL, including database design and optimization.

• I am familiar with SQL Server and have performed tasks such as backup and recovery.

• I have worked with PostgreSQL and have knowledge of advanced features like partitioning and replication.
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