Tech Mahindra Interview Questions, Process, and Tips

C++ ,Java , CAD , CNC programming, Data analytics

Q1. What product management ur doing
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Q2. Where did you undergo your technical traing
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Q3. Where did u place most of your focus when reviewing somebody else code
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Q4. What did you develop
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Q5. What was the project before you are doing
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Q1. Lets say you have table 1 with values 1,2,3,5,null,null,0 and table 2 has null,2,4,7,3,5 What would be the output after inner join?
Ans. 
The output after inner join of table 1 and table 2 will be 2,3,5.
• Inner join only includes rows that have matching values in both tables.

• Values 2, 3, and 5 are present in both tables, so they will be included in the output.

• Null values are not considered as matching values in inner join.
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Q2. Lets say you have customers table with customerID and customer name, Orders table with OrderId and CustomerID. write a query to find the customer name who placed the maximum orders. if more than one person...read more
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Q3. Spark Architecture, Optimisation techniques
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Q4. Some personal questions.
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Q1. Explain the entire architecture of a recent project you are working on in your organisation.
Ans. 
The project involves building a data pipeline to ingest, process, and analyze large volumes of data from various sources in Azure.
• Utilizing Azure Data Factory for data ingestion and orchestration

• Implementing Azure Databricks for data processing and transformation

• Storing processed data in Azure Data Lake Storage

• Using Azure Synapse Analytics for data warehousing and analytics

• Leveraging Azure DevOps for CI/CD pipeline aut
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Q2. How do you design an effective ADF pipeline and what all metrics and considerations you should keep in mind while designing?
Ans. 
Designing an effective ADF pipeline involves considering various metrics and factors.
• Understand the data sources and destinations

• Identify the dependencies between activities

• Optimize data movement and processing for performance

• Monitor and track pipeline execution for troubleshooting

• Consider security and compliance requirements

• Use parameterization and dynamic content for flexibility

• Implement error handling and retries fo
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Q3. Lets say you have a very huge data volume and in terms of performance how would you slice and dice the data in such a way that you can boost the performance?
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Q4. Lets say you have to reconstruct a table and we have to preserve the historical data ? ( i couldnt answer that but please refer to SCD)
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Q5. We have adf and databricks both, i can achieve transformation , fetching the data and loading the dimension layer using adf also but why do we use databricks if both have the similar functionality for few ...read more
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Q1. Basic HR questions
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Q1. What programming languages are you most familiar with?
Ans. 
I am most familiar with C++ and Python programming languages.
• C++

• Python
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Q2. How can you debug a program while it's being used?
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Debugging a program while it's being used requires using tools like logging, monitoring, and remote debugging.
• Use logging to track the flow of the program and identify any errors or issues.

• Implement monitoring tools to keep an eye on the program's performance and detect any anomalies in real-time.

• Utilize remote debugging techniques to troubleshoot and fix issues without interrupting the program's operation.

• Use breakpoi...read more
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Q3. Describe the troubleshooting process you'd follow for a crashing program.
Ans. 
I would start by checking for any error messages, reviewing recent changes, testing in a different environment, and consulting with colleagues.
• Check for any error messages or logs to identify the issue

• Review recent changes or updates that may have caused the program to crash

• Test the program in a different environment to see if the issue persists

• Consult with colleagues or experts for their input and suggestions
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Q4. What is your field of expertise and what would you like to learn more about?
Ans. 
My field of expertise is in mechanical maintenance, specifically in troubleshooting and repairing industrial machinery. I would like to learn more about predictive maintenance techniques and advanced automation systems.
• Expertise in troubleshooting and repairing industrial machinery

• Knowledge of preventive maintenance practices

• Interest in learning about predictive maintenance techniques

• Desire to explore advanced automati
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Q5. What’s the most effective way to gather user and system requirements?
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The most effective way to gather user and system requirements is through direct communication and collaboration.
• Engage with stakeholders to understand their needs and preferences

• Utilize surveys, interviews, and workshops to gather feedback

• Document requirements clearly and prioritize them based on importance

• Use prototyping and mockups to visualize the final product

• Regularly communicate and update stakeholders on the pro
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Q6. How would you troubleshoot a crashing program?
Ans. 
To troubleshoot a crashing program, I would start by checking for error messages, reviewing recent changes, testing in a different environment, and debugging the code.
• Check for error messages to identify the cause of the crash

• Review recent changes in the program or system that may have caused the crash

• Test the program in a different environment to see if the crash is environment-specific

• Debug the code to identify and f
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Q7. How do you handle pressure?
Ans. 
I handle pressure by staying organized, prioritizing tasks, and maintaining a positive attitude.
• I stay organized by creating to-do lists and breaking down tasks into manageable steps.

• I prioritize tasks based on deadlines and importance to ensure that critical tasks are completed first.

• I maintain a positive attitude by focusing on solutions rather than problems and taking breaks when needed to recharge.

• I communicate eff...read more
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Q1. What are the optimization techniques used in Spark?
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Q2. What methods do you use to transfer data from on-premises storage to Azure Data Lake Storage Gen2?
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Q1. Types of joins and spark queries
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Q1. What is your willingness to work in a firm office environment?
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Q1. Tell me about your self introduction
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Q2. Tell me about favourite place in india
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Q3. Tell me about your hobbies
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Q4. Your life expectiance
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Q5. Tell me abouts family
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Q6. Tell me about your strength
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Q7. Tell me about your childhood memories
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Q1. Difference between bigtable and bigquery.
Ans. 
Bigtable is a NoSQL database for real-time analytics, while BigQuery is a fully managed data warehouse for running SQL queries.
• Bigtable is a NoSQL database designed for real-time analytics and high throughput, while BigQuery is a fully managed data warehouse for running SQL queries.

• Bigtable is used for storing large amounts of semi-structured data, while BigQuery is used for analyzing structured data using SQL queries.

• ...read more
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Q2. How to remove duplicate rows from bigquery? find the month of a given date in bigquery.
Ans. 
To remove duplicate rows from BigQuery, use the DISTINCT keyword. To find the month of a given date, use the EXTRACT function.
• To remove duplicate rows, use SELECT DISTINCT * FROM table_name;

• To find the month of a given date, use SELECT EXTRACT(MONTH FROM date_column) AS month_name FROM table_name;

• Make sure to replace 'table_name' and 'date_column' with the appropriate values in your query.
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Q3. What operator is used in composer to move data from gcs to bq
Ans. 
The operator used in Composer to move data from GCS to BigQuery is the GCS to BigQuery operator.
• The GCS to BigQuery operator is used in Apache Airflow, which is the underlying technology of Composer.

• This operator allows you to transfer data from Google Cloud Storage (GCS) to BigQuery.

• You can specify the source and destination parameters in the operator to define the data transfer process.
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Q4. Write a code for this - input = [1,2,3,4] output = [1,4,9,16]
Ans. 
Code to square each element in the input array.
• Iterate through the input array and square each element.

• Store the squared values in a new array to get the desired output.
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Q5. Dataflow vs dataproc.
Ans. 
Dataflow is a fully managed stream and batch processing service, while Dataproc is a managed Apache Spark and Hadoop service.
• Dataflow is a serverless data processing service that automatically scales to handle your data, while Dataproc is a managed Spark and Hadoop service that requires you to provision and manage clusters.

• Dataflow is designed for both batch and stream processing, allowing you to process data in real-t...read more
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Q6. Architecture of bq. Query optimization techniques in bigquery.
Ans. 
BigQuery architecture includes storage, execution, and optimization components for efficient query processing.
• BigQuery stores data in Capacitor storage system for fast access.

• Query execution is distributed across multiple nodes for parallel processing.

• Query optimization techniques include partitioning tables, clustering tables, and using query cache.

• Using partitioned tables can help eliminate scanning unnecessary data.

• ...read more
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Q7. RDD vs dataframe vs dataset in pyspark
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RDD vs dataframe vs dataset in PySpark
• RDD (Resilient Distributed Dataset) is the basic abstraction in PySpark, representing a distributed collection of objects

• Dataframe is a distributed collection of data organized into named columns, similar to a table in a relational database

• Dataset is a distributed collection of data with the ability to use custom classes for type safety and user-defined functions

• Dataframes and Data...read more
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