Multisoft Virtual Academy offers a comprehensive training and certification course for Google BigQuery. This course equips participants with the necessary skills and knowledge to utilize the powerful capabilities of BigQuery for data analytics and processing. Through interactive virtual sessions, participants learn about data warehousing, querying, and optimizing performance using BigQuery. The training covers key concepts such as data modeling, data ingestion, and advanced analytics techniques. With experienced instructors and hands-on exercises, Multisoft Virtual Academy ensures a practical learning experience, enabling professionals to leverage BigQuery effectively. The certification course serves as a valuable credential for individuals looking to demonstrate their expertise in Google BigQuery.

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Google BigQuery Training
Certification

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About Multisoft
Take your skills to next level with Multisoft Virtual Academy, one of the leading
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companies, we offer world-class one-on-one and corporate trainings to empower
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and globally recognized training certificates.
About Course
Welcome to our in-depth Google BigQuery certification course by Multisoft Virtual
Academy, your gateway to mastering the art of data analysis and manipulation. This
comprehensive course, designed for data enthusiasts at all levels, provides an immersive
and hands-on experience in leveraging one of Google Cloud's most dynamic tools:
BigQuery.

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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

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 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

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 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 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

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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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