Google BigQuery Training

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Instructor-Led Training Parameters

Course Highlights

  • Instructor-led Online Training
  • Project Based Learning
  • Certified & Experienced Trainers
  • Course Completion Certificate
  • Lifetime e-Learning Access
  • 24x7 After Training Support

Google BigQuery Training Course Overview

Explore the World of Big Data Analytics: Google BigQuery Course by Multisoft Systems - Acquire in-depth knowledge and hands-on experience with Google's powerful BigQuery platform. Learn advanced data querying techniques, optimize performance, and unlock the potential of your data to gain valuable business insights. Take your data analytics skills to new heights with this comprehensive training program

The Google BigQuery course by Multisoft Systems provides a comprehensive overview of the platform and equips participants with the skills to effectively analyze and extract insights from large datasets. Participants will learn the fundamentals of BigQuery, including its features and how it fits into the Google Cloud Platform ecosystem. The course covers various topics such as data ingestion, advanced querying techniques, working with BigQuery SQL, data transformation and analysis, performance optimization, security, and data governance. Throughout the course, participants will gain hands-on experience with BigQuery, learning how to load data from various sources and write efficient queries to process large datasets. They will explore advanced SQL concepts, such as joins, aggregations, and window functions, and apply them to extract meaningful insights from their data. Participants will also learn techniques for data transformation, including cleansing, enrichment, and aggregation.

Performance optimization is a key focus of the course, teaching participants strategies to improve query performance, such as query caching, partition pruning, and query optimization techniques. They will gain an understanding of how to analyze query execution plans and identify bottlenecks for optimization. Security and data governance are also covered, ensuring participants understand best practices for securing data in BigQuery, controlling access, and enforcing data governance policies.
By the end of the course, participants will have a strong understanding of BigQuery's capabilities and be able to leverage it to perform advanced data analytics tasks, make informed decisions, and gain valuable insights from their datasets. They will be equipped with practical skills to optimize performance, ensure data security, and adhere to data governance practices in a BigQuery environment.

Google BigQuery Course Objective
  • Understand the fundamentals of Google BigQuery, its features, and its role in the Google Cloud Platform ecosystem.
  • Load and ingest data into BigQuery from various sources, including CSV files, JSON files, and Google Cloud Storage.
  • Perform advanced querying techniques using BigQuery SQL, including using SQL functions, joins, aggregations, and window functions.
  • Transform and analyze data in BigQuery, including data cleansing, enrichment, and aggregation.
  • Optimize query performance in BigQuery by utilizing query caching, partition pruning, and query optimization techniques.
  • Implement security measures to protect data in BigQuery, including access control, data encryption, and audit logging.
  • Adhere to data governance practices in BigQuery by enforcing policies and compliance with regulatory requirements.
Google BigQuery Online Training
  • Recorded Videos After Training
  • Digital Learning Material
  • Course Completion Certificate
  • 24x7 After Training Support
Target Audience
  • This course is for IT Professionals who want to learn about Google Cloud Technologies.
Google BigQuery Course Prerequisites
  • This course is for IT Professionals who want to learn about Google Cloud Technologies.
Google BigQuery Course Certification
  • Multisoft Systems provides a globally recognized training certificate after successful completion of Google BigQuery Course.

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Google BigQuery Training 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
  • 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 Tips
     

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Free Google BigQuery Training Assessment

This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :

  • User-friendly interface for easy navigation
  • Secure login and authentication measures to protect data
  • Automated scoring and grading to save time
  • Time limits and countdown timers to manage duration.
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Multisoft Systems is the “one-top learning platform” for everyone. Get trained with certified industry experts and receive a globally-recognized training certificate. Some Multisoft Training Certificate Features :

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  • Course ID & Course Name
  • Certificate with Date of Issuance
  • Name and Digital Signature of the Awardee
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Google BigQuery Training FAQ's

This course is designed for data analysts, data engineers, database administrators, and professionals involved in analyzing and extracting insights from large datasets using Google BigQuery.

There are no strict prerequisites for this course. However, a basic understanding of SQL and data concepts will be beneficial. Familiarity with cloud computing and the Google Cloud Platform (GCP) will also be helpful, but not mandatory.

Yes, this course includes hands-on exercises and practical examples to reinforce the concepts covered. Participants will have the opportunity to work with BigQuery, load data, write queries, and perform data analysis tasks.

The course is available in various formats, including online self-paced learning, instructor-led virtual classes, or in-person training. The format may vary depending on the training provider.

The course covers topics such as BigQuery fundamentals, data ingestion, advanced querying techniques, data transformation and analysis, performance optimization, security, and data governance in BigQuery.

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