Hitech Digital Solutions Data Analyst Trainee Interview Questions and Answers

Q1. What are different KPI's
Ans. 
Key Performance Indicators (KPIs) are measurable values that demonstrate how effectively a company is achieving key business objectives.
• KPIs are specific, measurable, achievable, relevant, and time-bound metrics used to evaluate the success of an organization or a particular activity.

• Examples of KPIs include revenue growth rate, customer acquisition cost, customer retention rate, website traffic, conversion rate, and e
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Q2. Differentiate loc and iloc in pandas
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loc is label-based indexing while iloc is integer-based indexing in pandas.
• loc is used to access a group of rows and columns by labels

• iloc is used to access a group of rows and columns by integer position

• Example: df.loc['row_label', 'column_label'] vs df.iloc[0, 1]
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Q1. What is Pyspark?
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Pyspark is a Python API for Apache Spark, a powerful open-source distributed computing system.
• Pyspark is used for processing large datasets in parallel across a cluster of computers.

• It provides high-level APIs in Python for Spark programming.

• Pyspark allows seamless integration with other Python libraries like Pandas and NumPy.

• Example: Using Pyspark to perform data analysis and machine learning tasks on big data sets.
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Q2. What is Pyspark SQL?
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Pyspark SQL is a module in Apache Spark that provides a SQL interface for working with structured data.
• Pyspark SQL allows users to run SQL queries on Spark dataframes.

• It provides a more concise and user-friendly way to interact with data compared to traditional Spark RDDs.

• Users can leverage the power of SQL for data manipulation and analysis within the Spark ecosystem.
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Q3. How to merge 2 dataframes of different schema?
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To merge 2 dataframes of different schema, use join operations or data transformation techniques.
• Use join operations like inner join, outer join, left join, or right join based on the requirement.

• Perform data transformation to align the schemas before merging.

• Use tools like Apache Spark, Pandas, or SQL to merge dataframes with different schemas.
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Q4. What is Pyspark streaming?
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Pyspark streaming is a scalable and fault-tolerant stream processing engine built on top of Apache Spark.
• Pyspark streaming allows for real-time processing of streaming data.

• It provides high-level APIs in Python for creating streaming applications.

• Pyspark streaming supports various data sources like Kafka, Flume, Kinesis, etc.

• It enables windowed computations and stateful processing for handling streaming data.

• Example: C...read more
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Q1. Tools and technologies that i have worked
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Q2. Coding part
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Q1. Tell me about yourself
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Q2. Why do you choose this job
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Q3. What’s your strength and weakness
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Q4. Are you ready to work in night shift
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Q5. What’s your short term goal
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Q6. What do you know about thryve digital
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Q1. Find duplicate rows in the given table
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Q1. Spark Architecture
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Q2. Explain the Spark architecture with example
Ans. 
Spark architecture includes driver, cluster manager, and worker nodes for distributed processing.
• Spark architecture consists of a driver program that manages the execution of tasks on worker nodes.

• Cluster manager is responsible for allocating resources and scheduling tasks across worker nodes.

• Worker nodes execute the tasks and store data in memory or disk for processing.

• Example: In a Spark application, the driver progr...read more
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1.ETL Pipeline
2.PySpark Code
3.SQL

Q1. 1.sql easy question 2.pyspark easy code as I was fesher
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Q2. 1.query related to group by
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Q1. 1.One tricky sql query 2.What is sqoop?sqoop performs which job - map or reduce?
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Q1. Questions on SQL complex queries
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Q2. Handling ADF pipelines
Ans. 
Handling ADF pipelines involves designing, building, and monitoring data pipelines in Azure Data Factory.
• Designing data pipelines using ADF UI or code

• Building pipelines with activities like copy data, data flow, and custom activities

• Monitoring pipeline runs and debugging issues

• Optimizing pipeline performance and scheduling triggers
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Q3. Schedules and triggers
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Q4. About project work and complexity faced and handling issues
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Q1. Salary discussion
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