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Tech Mahindra
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I applied via Naukri.com and was interviewed in Nov 2024. There were 2 interview rounds.
Developed a data pipeline to ingest, process, and analyze customer feedback data for a retail company.
Used Google Cloud Platform services like BigQuery, Dataflow, and Pub/Sub for data processing.
Implemented data cleansing and transformation techniques to ensure data quality.
Created visualizations and dashboards using tools like Data Studio for stakeholders to easily interpret the data.
GCP offers different storage classes for varying performance and cost requirements.
Standard Storage: for frequently accessed data
Nearline Storage: for data accessed less frequently
Coldline Storage: for data accessed very infrequently
Archive Storage: for data stored for long-term retention
SQL optimization techniques focus on improving query performance by reducing execution time and resource usage.
Use indexes to speed up data retrieval
Avoid using SELECT * and instead specify only the columns needed
Optimize joins by using appropriate join types and conditions
Limit the use of subqueries and instead use JOINs where possible
Use EXPLAIN to analyze query execution plans and identify bottlenecks
select * from table limit 100 is faster
Using 'select * from table' retrieves all rows from the table, which can be slower if the table is large
Using 'select * from table limit 100' limits the number of rows retrieved, making it faster
Limiting the number of rows fetched can improve query performance
SCD stands for Slowly Changing Dimension and Merge is a SQL operation used to update or insert data in BigQuery.
SCD is used to track changes to data over time in a data warehouse
Merge in BigQuery is used to perform insert, update, or delete operations in a single statement
Example: MERGE INTO target_table USING source_table ON condition WHEN MATCHED THEN UPDATE SET col1 = value1 WHEN NOT MATCHED THEN INSERT (col1, col2)
BigQuery is a fully managed, serverless data warehouse that enables scalable analysis over petabytes of data.
BigQuery uses a columnar storage format for efficient querying.
It supports standard SQL for querying data.
BigQuery allows for real-time data streaming for analysis.
It integrates with various data sources like Google Cloud Storage, Google Sheets, etc.
BigQuery provides automatic scaling and high availability.
Dataflow function to split sentence
Use the Split transform in Dataflow to split the sentence into words
Apply ParDo function to process each word individually
Use regular expressions to handle punctuation and special characters
The GCP services used in our project include BigQuery, Dataflow, Pub/Sub, and Cloud Storage.
BigQuery for data warehousing and analytics
Dataflow for real-time data processing
Pub/Sub for messaging and event ingestion
Cloud Storage for storing data and files
Cloud Functions are event-driven functions that run in response to cloud events.
Serverless functions that automatically scale based on demand
Can be triggered by events from various cloud services
Supports multiple programming languages like Node.js, Python, etc.
To schedule a job to trigger every hour in Airflow, you can use the Cron schedule interval
Define a DAG (Directed Acyclic Graph) in Airflow
Set the schedule_interval parameter to '0 * * * *' to trigger the job every hour
Example: schedule_interval='0 * * * *'
Use Python's slicing feature to display a string in reverse order.
Use string slicing with a step of -1 to reverse the string.
Example: 'hello'[::-1] will output 'olleh'.
Pub/Sub is a messaging service that allows communication between independent applications.
Pub/Sub is used for real-time messaging and event-driven systems.
It is commonly used for data ingestion, streaming analytics, and event-driven architectures.
Examples of Pub/Sub services include Google Cloud Pub/Sub, Apache Kafka, and Amazon SNS/SQS.
I applied via LinkedIn and was interviewed in Oct 2024. There were 2 interview rounds.
I have experience working on projects involving data processing, transformation, and analysis using GCP services like BigQuery, Dataflow, and Dataproc.
Utilized BigQuery for storing and querying large datasets
Implemented data pipelines using Dataflow for real-time data processing
Utilized Dataproc for running Apache Spark and Hadoop clusters for data processing
Worked on data ingestion and transformation using Cloud Stora
I applied via Naukri.com and was interviewed in Oct 2024. There was 1 interview round.
IAM is Identity and Access Management, SA is Service Account, BigQuery is a data warehouse, QlikSense is a data visualization tool, GitHub is a version control system, Spark is a distributed computing framework, Airflow is a workflow automation tool, Bigtable is a NoSQL database, Cloud Composer is a managed workflow orchestration service, Pub/Sub is a messaging service.
IAM is used to manage access to resources in Googl...
I applied via Naukri.com and was interviewed in Jun 2024. There was 1 interview round.
Check if a string is a palindrome or not
Compare the string with its reverse to check for palindrome
Ignore spaces and punctuation marks when comparing
Examples: 'racecar' is a palindrome, 'hello' is not
Use Python to create a GCS bucket
Import the necessary libraries like google.cloud.storage
Authenticate using service account credentials
Use the library functions to create a new bucket
Python code to trigger a dataflow job in cloud function
Use the googleapiclient library to interact with the Dataflow API
Authenticate using service account credentials
Submit a job to Dataflow using the projects.locations.templates.launch endpoint
Use SQL to find keys present in table A but not in table B (old copy of A).
Use a LEFT JOIN to combine tables A and B based on the key column
Filter the results where the key column in table B is NULL
This will give you the keys present in table A but not in table B
Use GCP Dataflow to transfer files between GCS buckets
Create a Dataflow pipeline using Apache Beam to read from source bucket and write to destination bucket
Use GCS connector to read and write files in Dataflow pipeline
Set up appropriate permissions for Dataflow service account to access both buckets
Cloud Composer is another orchestration tool in GCP
Cloud Composer is a fully managed workflow orchestration service built on Apache Airflow
It allows you to author, schedule, and monitor workflows that span across GCP services
Cloud Composer provides a rich set of features like DAGs, plugins, and monitoring capabilities
It integrates seamlessly with other GCP services like BigQuery, Dataflow, and Dataproc
I applied via Company Website and was interviewed in Sep 2023. There were 3 interview rounds.
BigQuery is used for analyzing large datasets and running complex queries, while SQL is used for querying databases.
BigQuery is used for analyzing large datasets quickly and efficiently
SQL is used for querying databases to retrieve specific data
BigQuery can handle petabytes of data, making it ideal for big data analysis
SQL can be used to perform operations like filtering, sorting, and aggregating data
I applied via Company Website and was interviewed before Mar 2023. There were 2 interview rounds.
SQL joins are used to combine rows from two or more tables based on a related column between them.
SQL joins are used to retrieve data from multiple tables based on a related column between them
Types of SQL joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN
In BigQuery, joins can be performed using standard SQL syntax
Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column
I applied via LinkedIn and was interviewed before Nov 2021. There were 3 interview rounds.
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