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Introduction to BigQuery

Unlock BigQuery's power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.

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Course Description

Delve into the core concepts of BigQuery architecture, understanding its historical significance and comparing it to traditional database systems. Uncover the diverse range of applications where BigQuery shines, setting the stage for a deeper exploration of its capabilities.

Mastering Analytical Queries and Data Manipulation

Learn to wield the power of BigQuery by executing analytical queries and manipulating data with precision. Navigate datasets and tables effortlessly while gaining proficiency in utilizing bq command line tools for data ingestion. Dive into the complexities of data types and unstructured data, honing your skills to extract meaningful insights.

Optimizing Workflow Efficiency and Query Performance

Elevate your data analysis workflow to new heights by mastering advanced techniques within BigQuery. From optimizing query performance through strategic optimization strategies to mastering the intricacies of joining data, this section equips you with the tools needed to streamline your analytical processes. Unlock the potential of Data Manipulation Language (DML) statements, empowering you to perform complex data transformations with ease.
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  1. 1

    BigQuery Architecture and Structure

    Free

    In this chapter, you will learn about the unique features of BigQuery, how it runs large analytical queries, and how it compares to other data warehouses and databases.

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    Introduction to BigQuery
    50 xp
    Unique attributes of BigQuery
    50 xp
    BigQuery, Snowflake, and Redshift
    100 xp
    BigQuery compared to a traditional SQL database
    100 xp
    Starting with e-commerce
    100 xp
    BigQuery Architecture
    50 xp
    Classifying BigQuery components
    100 xp
    Ordering the BigQuery architecture
    100 xp
    Execution trees inside Dremel
    100 xp
    BigQuery data organization
    50 xp
    Table structure
    100 xp
    BigQuery data rules
    50 xp
    Tables in the wild
    100 xp
  2. 2

    Writing queries and data types

    This chapter will cover the fundamentals of how to write queries in BigQuery while also providing a review of SQL concepts. You will also learn how to ingest bulk data into BigQuery and the different data types within BigQuery.

    Play Chapter Now
    Writing queries in BigQuery
    50 xp
    Exploring the course data with SQL
    100 xp
    Finding order total value
    100 xp
    Using joins
    100 xp
    Data ingestion in BigQuery
    50 xp
    Loading local data to BigQuery
    50 xp
    Acceptable data formats
    100 xp
    Structuring a LOAD DATA statement
    100 xp
    Date/time types in BigQuery
    50 xp
    Formatting dates for reports
    100 xp
    Formatting timestamps and dates
    100 xp
    Finding data within certain ranges
    100 xp
    Using CURRENT_TIMESTAMP
    100 xp
    Unstructured data
    50 xp
    Create an array in a query
    100 xp
    Use SEARCH with unstructured data
    100 xp
    UNNEST-ing Data
    100 xp
  3. 3

    Querying data in BigQuery

    Learn how to query data using common table expressions, aggregations, and window functions.

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    Common table expressions
    50 xp
    Filtering data with CTEs
    100 xp
    Optimizing using CTEs
    100 xp
    Using multiple CTEs
    100 xp
    Aggregations
    50 xp
    Classifying aggregate functions
    100 xp
    Using COUNTIF
    100 xp
    Filtering with HAVING
    100 xp
    ANY_VALUE
    100 xp
    Special aggregations in BigQuery
    50 xp
    Logical aggregates
    100 xp
    Using STRING_AGG and ARRAY_CONCAT_AGG
    100 xp
    Approximate statistical functions
    100 xp
    WINDOW Functions
    50 xp
    Writing a window query
    100 xp
    RANK and LEAD/LAG
    100 xp
    Using row based WINDOW functions
    100 xp
    Filtering with QUALIFY
    100 xp
  4. 4

    Data management and optimization

    Understand all join types in BigQuery, mange data with data manipulation, and optimize your queries.

    Play Chapter Now
    Joins in BigQuery
    50 xp
    Finding the correct join type
    50 xp
    RIGHT, LEFT, and OUTER joins
    100 xp
    UNNEST with CROSS JOINs
    100 xp
    Joins with aggregations
    100 xp
    Data manipulation language (DML) statements
    50 xp
    Data manipulation types
    50 xp
    Using conditions in DML statements
    100 xp
    Considerations using DML statements
    100 xp
    Query optimization strategies
    50 xp
    Limiting the amount of data
    100 xp
    Finding the last 90 days of orders
    100 xp
    Perform optimizations in BigQuery
    100 xp
    Congratulations!
    50 xp
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collaborators

Collaborator's avatar
Katerina Zahradova
Collaborator's avatar
Arne Warnke

prerequisites

Data Manipulation in SQL
Matt Forrest HeadshotMatt Forrest

Field CTO

Matt Forrest, Field CTO at CARTO, champions innovation and learning in the tech sphere. With over 13 years of expertise, he guides individuals and organizations to advance their technical careers. His commitment to knowledge sharing is evident in his recent publication on Spatial SQL, highlighting his dedication to fostering technological progress.
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