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BigQuery for Data Science

Analyze Data in an Optimized way at Google Scale


3 Days


Intermediate Level

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The purpose of this course is to provide participants with knowledge and skills essential to work with BigQuery in an optimal manner. The participants will understand how BigQuery works, its Architecture, Best Practices and how to optimize it for minimizing the cost and reducing the query runtime. 

The lab exercises of the course will be performed using Jupyter Lab Environment.

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  • Data Analysts
  • Data Engineers
  • Data Scientists
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  • Features of Big Query
  • Big Query Architecture
  • How BigQuery stores data
  • How does a query execute on BQ?
  • Various APIs in BQ
  • Bootstrapping Lab Environment
  • Ways to interact with BigQuery
  • BQ Command line interface
  • Exploring BigQuery Dataset & Tables
  • BigQuery Table Types
  • Wildcard Tables & its limitations
  • Query Execution Plan
  • Writing Effective Queries
  • With Clause in BigQuery
  • BigQuery Core – Python Client API
  • Understanding Query Metadata
  • Caching in BigQuery
  • Time Travels and 
  • Table Snapshots
  • Table Clones
  • Extending BQ
  • Approach of Data Modeling
  • Denormalized Tables
  • Understanding Key Data Formats
  • Solving Data Skew Problem
  • Working with Views
  • Using Materialized Views
  • Scope of Optimizations
  • Ways to Optimize Big Query
  • Understanding Slots & BigQuery Pricing
  • Diagnose Query Performance Issues
  • Query Plan Analysis
  • Understanding Partitioning
  • Key considerations for Partitioning
  • Making use of Partitioning
  • Benefits of Clustering
  • Key considerations for Clustering
  • Making use of Clustered Tables
  • When to prefer Partitioning, Clustering, or Both
  • Exploring Indexing Capability 
  • Exploring Join and Best Practices
  • Nested & Repeated Data
  • Best Practices for BigQuery
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Participants must have knowledge of –

  1. SQL query language
  2. Data Warehousing concepts
  3. Jupyter Notebook Environment
  4. Python Basics

Knowledge of “Basics of BigQuery” will be a plus.


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