Google Cloud Bigquery Training Course Singapore

The architectural patterns you explore show how Google Cloud can enable you to move beyond traditional data warehousing practices.

This 4 day instructor-led class teaches course participants Learn about the Product Deep Dive for Google Big Query as Cloud Data warehouse platform. Discuss general concepts that are applicable to any data warehousing

    BigQuery is Google’s fully managed, petabyte-scale, low-cost analytics data warehouse. It is an enterprise data warehouse that solves storing and querying massive datasets by enabling super-fast SQL queries using the processing power of Google’s Infrastructure. Delegates can access BigQuery by using command-line, by using Classic web UI or GCP console, or by making calls to the BigQuery REST API using a variety of client libraries such as Java, .NET, or Python.

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    Course Description

    This course teaches delegates about running and managing jobs, working with datasets, table schema, partitioned tables, clustered tables, and views. Delegates will acquire knowledge of how to add, view, update, filter, and delete labels in BigQuery resources. This course describes how to load data into BigQuery and querying BigQuery data. Delegates will learn how to query externally partitioned data, federated queries with cloud SQL data, query cloud big table data, cloud storage, and Google drive data. In addition, delegates will also gain an understanding of controlling BigQuery costs, securing BigQuery resources, monitoring, logging and BigQuery API.

    Learning Objectives

    • Learn how to work with data sets, table schemas and partitioned tables.
    • Gain a comprehensive knowledge of how to load data into BigQuery.
    • Learn to query BigQuery data, external data sources, and secure big query resources.

    Certification Curriculum

    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
    • Estimating Storage and Query Costs
    • Custom Cost Controls
    Module 14
    Securing BigQuery Resources
    • Access Controls
    • Encryption at Rest
    • Using Cloud DLP to Scan BigQuery Data
    • Protecting Data with Cloud KMS Keys
    • BigQuery Monitoring Using Stackdriver
    Module 15
    BigQuery API Basics
    • Authentication
    • Authorising API Requests
    • Batch Requests
    • Paging through Tables
    • API Performance Tip


    • Experience in Database
    • Familiarity with SQL
    • Google Cloud Platform

    Download Brochure

    Join Google Cloud BigQuery Training Course Singapore and gain the knowledge and skills needed to start a career in Bigquery.

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    Certification Assessment

    When you complete this course, you’ll earn a Certificate to share with your professional network as well as unlock access to career support resources to help you kickstart your new career. You can find more information on individual Professional Certificates from Google Cloud Certification where it applies.

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    Training FAQ's

    Is this training conducted as an online/ virtual course?

    As a response to the COVID-19, we have moved our classes online. Our Live Virtual format delivers the same benefits as our face-to-face training: expert instruction, hands-on labs and exercises, peer-to-peer collaboration, and high-quality instructional material.

    If I cancel the enrollment, will I get a refund?

    Cancellation requests received within 24 hours of registration would be offered a full refund (minus payment gateway charges), please reach out to our support team through drop a refund request to Visit our page for more details about Cancellation & Refund Policy.

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    The process of enrolling for this classroom training is simple. The payment can be made through different options by using a debit/credit card which includes MasterCard, Visa Card, American Express or through PayPal. Acknowledgment will be issued automatically via email to the candidates once payment is done.

    What are the modes of payment available for payment of accreditation fees?

    Payment can be made via credit card, debit card, UPI, and internet banking.

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