Google BigQuery Training

The Google BigQuery Training course equips learners with the skills to use BigQuery for efficient data analysis and management. It covers querying, optimisation, and advanced analytics, enabling professionals to harness BigQuery for large-scale data processing.

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Learning Options

Online self paced
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Online Video-Based Learning
Flexible Schedule
Expert Trainers with Industry Experience
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Overview

The Google BigQuery Training course is designed to help professionals master Google BigQuery, a powerful cloud-based data warehouse. This course provides in-depth knowledge of BigQuery’s capabilities, enabling learners to analyse and manage large datasets effectively.

BigQuery is widely used for its scalability, speed, and ability to handle complex queries on massive datasets. This course covers essential topics such as querying and exploring datasets, performance optimisation, and leveraging BigQuery for advanced analytics. Learners will gain practical experience in using BigQuery’s SQL-like syntax and integrating it with other Google Cloud services.

This 2-day training offered by MPES includes expert-led sessions, hands-on exercises, and real-world case studies. Learners will develop the skills to use BigQuery for data-driven decision-making, enabling them to address complex analytical challenges in various industries.

Course Objectives

Understand the fundamentals of Google BigQuery and its applications
Develop skills in querying and managing large datasets using BigQuery
Learn to optimise query performance and minimise costs
Gain expertise in integrating BigQuery with Google Cloud services
Apply BigQuery to real-world analytics and data visualisation tasks

Upon completion, learners will be equipped to use BigQuery effectively for large-scale data processing and analytics, enhancing their ability to deliver actionable insights.

Average completion time

2 Month

with unlimited support

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Course Includes

Course Details

Develop your understanding of essential financial, business and management accounting techniques with ACCA Applied Knowledge. You'll learn basic business and management principles and the skills required of an accountant working in business.

Entry Requirements

Educational Background: A basic understanding of data analysis and database management is recommended.
Technical Proficiency: Familiarity with SQL and Google Cloud tools will enhance understanding.
Interest in Data Analytics: Ideal for professionals and learners aiming to leverage BigQuery for large-scale data analysis.

Learning Outcomes

Master BigQuery Basics: Gain a comprehensive understanding of BigQuery’s architecture and functionality.
Develop Querying Skills: Learn to write efficient queries and manage datasets in BigQuery.
Optimise Performance: Build expertise in query performance tuning and cost management.
Integrate with Cloud Services: Use BigQuery with other Google Cloud tools for seamless data processing and analytics.

Target Audience

The Google BigQuery Training course is designed for professionals seeking to enhance their data analysis skills. It provides practical knowledge to efficiently query, manage, and analyse large datasets using Google BigQuery’s powerful tools. Below are the individuals who will benefit from this course:

Data Analysts
Business Intelligence Professionals
Data Scientists
Cloud Architects
Database Administrators
Technology Consultants
Software Developers

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
Modifying Table Schemas
Manually Changing Table Schemas

Module 5: Working with 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
Managing and Querying Partitioned Tables
Using DML with Partitioned Tables

Module 7: Working with Clustered Tables

Define Clustered Tables
Creating and Using Clustered Tables

Module 8: Working with Views

Introduction to Views
Creating a View
Controlling Access to Views
Creating Authorised Views
Listing Views
Updating View Properties
Managing Views

Module 9: Labelling 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 Local File

Module 11: Querying BigQuery Data

Running Interactive and Batch Queries
Writing Query Results
Using Cached Results
Querying Data Using a Wildcard Table
Saving and Sharing Queries
Scheduling Queries
Using the Query Plan Explanation

Module 12: Querying External Data Sources

Querying Cloud Bigtable
Querying Google Cloud Drive Data

Module 13: Controlling BigQuery Costs

Estimating Storage and Query Costs
Custom Cost Controls

Module 14: Securing BigQuery Resources

Encryption at Rest
Using Cloud DLP to Scan BigQuery Data

Module 15: BigQuery API Basics

Authentication
Batch Requests
Paging Through Tables
API Performance Tips

MPES Support That Helps You Succeed

At MPES, we offer comprehensive support to help you succeed in your studies. With expert guidance and valuable resources, we help you stay on track throughout your course.

MPES Learning offers dedicated support to help you succeed in Accounting and Finance courses.
Get expert guidance from tutors available online to assist with your studies.
Check your eligibility for exemptions with the relevant professional body before starting.
Our supportive team is here to offer study advice and support throughout your course.
Access a range of materials to help enhance your learning experience. These resources include practice exercises and additional reading to support your progress.

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