Course curriculum

    1. Segment 1 - Introduction to the Instructor

    2. Segment 2 - Introduction to BigQuery

    3. Segment 3 - Setting Up and Accessing BigQuery

    4. Segment 4 - Navigating the BigQuery UI

    5. Segment 5 - Exploring "bigquery-public-data" datasets

    1. Segment 6 - Introduction to Data Warehousing and BigQuery

    2. Segment 7 - Creating Datasets for Data Organization

    3. Segment 8 - Defining Tables with Schema and Settings

    4. Segment 9 - Partitioning and Clustering Strategies

    5. Segment 10 - Creating Tables using SQL

    6. Segment 11 - Creating Partitioned Tables using SQL

    1. Segment 12 - Installing Anaconda Package and Configuring Credentials

    2. Segment 13 - Introduction to Jupyter Notebook UI

    3. Segment 14 - Manipulating Data with Pandas: Replacing and Appending Tables

    4. Segment 15 - Adding Schema Information Dynamically

    5. Segment 16 - Incorporating Partitioning and Clustering Configurations

    1. Segment 17 - Understanding ETL (Extract, Transform, Load)

    2. Segment 18 - Performing ETL with CSV, Excel, and JSON files

    1. Segment 19 - Introduction to Data Query Language

    2. Segment 20 - Exploring SQL Examples for Data Retrieval

    3. Segment 21 - Leveraging Aggregate and Window Functions for Advanced Queries

    4. Segment 22 - User-Defined Functions (UDFs) for Custom Transformations

    5. Segment 23 - Data Security and Governance Best Practice

    6. Segment 24 - Conclusion

About this course

  • Free
  • 24 lessons
  • 2 hours of video content

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