Top Tiger Analytics SQL Interview Questions and Boost Your Data Engineering Career in 2024!
Are you preparing for a data engineering interview at Tiger Analytics? You've come to the right place! This comprehensive guide covers essential pyspark interview questions and provides in-depth answers to help you succeed in your upcoming interview. Whether you're a seasoned professional or just starting your career in data engineering, this video is packed with valuable insights to give you a competitive edge.
🔍 What You'll Learn:
Recent pyspark questions for Tiger Analytics interviews
Real-world data engineering scenarios and solutions
Expert tips for acing your technical interview
Insider knowledge on Tiger Analytics's interview process
Hands-on practice with sample SQL queries
📊 Sample Data :
Let's dive into a practical example that you might encounter in your Tiger Analytics interview:
data = [('TV', '2016-11-27', 800),('TV', '2016-11-30', 900),('TV', '2016-12-29', 500),('TV', '2017-11-20', 400),('FRIDGE', '2016-10-11', 760),('FRIDGE', '2016-10-13', 400),('FRIDGE', '2016-11-27',460)]
schema = ['product','sale_date','amount']
data1 = [('20d75c97-5fee-11e8-92c7-67fe1c388607',['A:X:M', 'B:Y:N', 'C:Z:O', 'D:W:P', 'E:V:Q','A:W:P']),('20d75c98-5fee-11e8-92c7-5f0316c1a74f',['A:X:M', 'B:W:N', 'C:L:O']),('20d75c99-5fee-11e8-92c7-d9bfa897a151',['A:X:M', 'F:Y:N', 'H:Z:O','A:W:P'])]
schema1 = ['uniqueid','status_value']
data2 = [(123, 'impression', '07/18/2022
11:36:12'),(123, 'impression', '07/18/2022
11:37:12'),(123, 'click', '07/18/2022
11:37:42'),(234, 'impression', '07/18/2022
14:15:12'),(234, 'click', '07/18/2022
14:16:12')]
schema2 = ['app_id','event_type','timestamp']
🚀 Key Topics Covered:
Advanced pyspark conceps
Aggregation and window functions
Data modeling best practices
Performance tuning for large datasets
Dealing with data inconsistencies and duplicates
💡 Interview Success Strategies:
Understand the interviewer's perspective
Showcase your problem-solving skills
Communicate your thought process effectively
Demonstrate your knowledge of data engineering principles
Highlight relevant projects and experiences
🔗 Additional Resources:
To further enhance your preparation, check out these playlists:
PySpark playlist : https://www.youtube.com/playlist?list=PL7DrGo85HcssOo4q5ihH3PqRRXwupRe65
Azure Datafactory playlist : https://youtube.com/playlist?list=PL7DrGo85HcsueO7qbe3-W9kGa00ifeQMn&si=IVjV6k5Yzr_xaU6p
PySpark RealTime Scenarios playlist : https://www.youtube.com/playlist?list=PL7DrGo85HcstBR0D4881RTIzqpwyae1Tl
Azure Data Factory RealTime Scenarios playlist : https://youtube.com/playlist?list=PL7DrGo85HcsulFTAXy2cgcS6bWRlIsHnn&si=LkXbqEKnHxCxHv2z
PySpark Interview Question : https://youtube.com/playlist?list=PL7DrGo85Hcssd_NsYufl8K7T8VSuZUy8j&si=JRNPFXUTdCb17RF4
Scenario Based Interview Question : https://youtube.com/playlist?list=PL7DrGo85Hcsu_Qbtbp373uhUVODcs-XAP&si=tOEjYgFTT1ZeJnY3
Unit Testing in PySpark : https://youtube.com/playlist?list=PL7DrGo85HcsuiY6C_08z_9jHoO_j3ZTe0&si=_A1-xVcN0fhZ6gr4
🌟 Why This Video Stands Out:
Up-to-date content reflecting Tiger Analytics's latest interview trends
In-depth explanations of complex SQL concepts
Real-world examples from experienced data engineers
Interactive coding demonstrations
Tips for both technical and soft skills required for success
👨💻 About the Instructor:
As an experienced data engineer and interview coach, I've helped countless professionals land their dream jobs at top tech companies like Tiger Analytics. My practical approach and industry insights will give you the confidence to excel in your interview.
🔔 Stay Connected:
Don't miss out on future interview tips and data engineering content! Subscribe to this channel and hit the notification bell to stay updated.
GitHub Repository: https://github.com/Pritamsaha627/Pyspark
LinkedIn Profile: https://www.linkedin.com/in/pritam-saha-060516139/
Telegram Channel: https://t.me/CognitiveCoders
WhatsApp Channel: https://whatsapp.com/channel/0029Va4x4s43bbUwjElGHS3X
Instagram : https://www.instagram.com/pritamsaha627
📧 Need Personalized Guidance?
For one-on-one coaching or specific interview questions, feel free to reach out:
Email:
[email protected]
Topmate: https://topmate.io/pritamsaha627
Remember, success in data engineering interviews comes from consistent practice and a deep understanding of core concepts. This video is your first step towards acing your Tiger Analytics interview and launching your dream career in data engineering.
Like, share, and subscribe for more valuable content on data engineering, pyspark, SQL and tech interviews. Your support motivates us to create high-quality, informative videos to help you succeed in your career journey.
1 Subscriber, 1👍🏻, 1Comment = 100 Motivation 🙏🏼
🙏🏻Please Subscribe 🙏🏼
#TigerAnalytics #DataEngineering #InterviewQuestions #DataEngineer #TechInterviews
5.818 Lượt nghe
Video
