| 01 table creation script.sql | 2.8 KB | ||
| 1 - Google-BigQuery-Notes.pdf | 1.4 MB | ||
| 1 - Running Notes PDF.html | 102.4 B | ||
| 10 - Assignment Social Media Case study.mkv | 102.8 MB | ||
| 2 - Sample Datasets.html | 102.4 B | ||
| 3 - BigQuery Introduction.mkv | 370.2 MB | ||
| 4 - Various Methods of Creating Tables in BigQuery Table Types Native External.mkv | 375.7 MB | ||
| 5 - Storage Optimization Techniques Partitioning Clustering with examples.mkv | 330.4 MB | ||
| 6 - Working with Complex data in BigQuery with examples JSONARRAY.mkv | 445.9 MB | ||
| 7 - Spotify Case Study session1.mkv | 356.2 MB | ||
| 8 - Spotify Case Study session2.mkv | 358.1 MB | ||
| 9 - Views Logical Views Materialized Views and Authorized Views with Examples.mkv | 348.3 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| bookmarks.sql | 2.3 KB | ||
| comment_likes.sql | 4.6 KB | ||
| comments.sql | 9 KB | ||
| customer-data.json | 77.5 KB | ||
| dataset_playlist_2010to2022.csv | 629.1 KB | ||
| department.txt | 102.4 B | ||
| employee.txt | 102.4 B | ||
| employee_data.json | 102.4 B | ||
| export_001.parquet | 14 KB | ||
| follows.sql | 23.2 KB | ||
| hashtag_follow.sql | 409.6 B | ||
| hashtags.sql | 716.8 B | ||
| login.sql | 2.8 KB | ||
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| photos.sql | 2.2 KB | ||
| post.sql | 6.6 KB | ||
| post_likes.sql | 18 KB | ||
| post_tags.sql | 4.4 KB | ||
| product-details.json | 17.2 KB | ||
| products.txt | 102.4 B | ||
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| sales_transactions.txt | 102.4 B | ||
| sampleJsn.json | 307.2 B | ||
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| transactions.csv | 307.2 B | ||
| twitter.avro | 512 B | ||
| usedata.txt | 204.8 B | ||
| user_data.csv | 307.2 B | ||
| user_events.csv | 307.2 B | ||
| user_events_schema.json | 307.2 B | ||
| users.sql | 5.5 KB | ||
| videos.sql | 3.1 KB | ||
| ▲ 48 total files | |||
Google Bigquery - From Basics To Advanced With Case Studies
https://WebToolTip.com
Published 7/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.63 GB | Duration: 7h 41m
Master Google BigQuery with lot of examples and real-world case studies
What you'll learn
Understand the fundamentals of Google BigQuery, including architecture, storage, and pricing
Load and manage data efficiently using various methods such as Cloud Storage, SDK, Console and streaming inserts.
Apply advanced concepts like partitioning, clustering, and working with arrays
Implement a complete end-to-end case study to simulate a real-world data analytics pipeline using BigQuery.
Requirements
Basic understanding of SQL is helpful, but not mandatory.
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