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by fatima
Price: 80,000
2 Months
0 Lessons

Google BigQuery

Google BigQuery Training

BigQuery is a fully-managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and intelligent caching for business intelligence. This learning path will first show you the fundamentals of how to use BigQuery and then how to optimize BigQuery to reduce costs, speed up your queries, and apply proper access control.

 


Learning Objectives

  • Load data into BigQuery using files or by streaming one record at a time
  • Run a query using standard SQL and save your results to a table
  • Export data from BigQuery using Google Cloud Storage
  • Reduce your BigQuery costs by reducing the amount of data processed by your queries
  • Create, load, and query partitioned tables for daily time-series data
  • Speed up your queries by using denormalized data structures, with or without nested repeated fields
  • Implement fine-grained access control using roles and authorized views

Course Content: 

Module 1: Interacting with BigQuery

● Introduction to BigQuery
● BigQuery Sandbox and Web UI
● Command-Line Tools
● BigQuery Classic Web UI


Module 2: Running and Managing Jobs
● Introduction
● Running Jobs Programmatically
● Managing Jobs


Module 3: Working with Datasets
● Define Datasets
● Dataset Locations
● Creating and Copying Datasets
● Controlling Access to Datasets
● Listing Datasets
● Updating Dataset Properties
● Managing Datasets
● Availability and Durability


Module 4: Working with Table Schemas
● Specifying a Schema
● Specifying Nested and Repeated Columns
● Auto-Detecting Schemas
● Modifying Table Schemas
● Manually Changing Table Schemas


Module 5: Working with Tables
● Creating and Using Tables
● Managing Tables and Table Data
● Exporting Table Data
● Updating Table Data using DML


Module 6: Working with Partitioned Tables
● What are Partitioned Tables?
● Creating Ingestion-time Partitioned Tables
● Creating Date/Time Partitioned Tables
● Creating Integer Range Partitioned Tables
● Managing and Querying Partitioned Tables
● Using DML with Partitioned Tables


Module 7: Working with Clustered Tables
● Define Clustered Tables
● Creating and Using Clustered Tables
● Querying Clustered Tables


Module 8: Working with Views
● Introduction to Views
● Creating Views
● Controlling Access to Views
● Creating Authorised Views
● Listing Views
● Updating View Properties
● Managing Views


Module 9: Labeling BigQuery Resources
● Adding Labels
● Viewing Labels
● Updating Labels
● Filtering Using Labels
● Deleting Labels


Module 10: Loading Data into BigQuery
● Loading Data from Cloud Storage
● Loading Data from a Local File
● Streaming Data into BigQuery


Module 11: Querying BigQuery Data
● Running Interactive and Batch Queries
● Performing a Query Dry Run
● Writing Query Results
● Using Cached Results
● Running Parameterised Queries
● Querying Data Using a Wildcard Table
● Saving and Sharing Queries
● Scheduling Queries
● Using the Query Plan Explanation
● Using the BigQuery Connector for Excel


Module 12: Querying External Data Sources
● Creating a Table Definition File
● Querying Externally Partitioned Data
● Federated Queries with Cloud SQL Data
● Querying Cloud Bigtable and Storage Data
● Querying Google Cloud Drive Data


Module 13: Controlling BigQuery Costs
● Introduction to BigQuery Costs


Intended Audience
  • Anyone who is interested in analyzing data on Google Cloud Platform

Prerequisites
  • Experience with databases
  • Familiarity with writing queries using SQL is recommended

INTERNATIONAL STUDENT FEE 300$ USD 


KEY FEATURES

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Flexible Classes Schedule

Online Classes for out of city / country students

Unlimited Learning - FREE Workshops

FREE Practice Exam

Internships Available

Free Course Recordings Videos

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