Drive Team Excellence with Google BigQuery Corporate Training

Empower your teams with expert-led on-site/in-house or virtual/online Google BigQuery Training through Edstellar, a premier Google BigQuery training company for organizations globally. Our customized training program equips your employees with the skills, knowledge, and cutting-edge tools needed for success. Designed to meet your specific training needs, this Google BigQuery group training program ensures your team is primed to drive your business goals. Transform your workforce into a beacon of productivity and efficiency.

BigQuery is a service provided by Google Cloud Platform, a suite of products & services on Google's scalable infrastructure that includes application hosting, cloud computing, and database services. 

Empower the workforce with our immersive and dynamic Google BigQuery training course, meticulously designed to turbocharge your corporate team's data prowess. In the age of data-driven decisions, staying ahead demands mastering tools like Google BigQuery, and we've got you covered. Our Google BigQuery instructor-led training goes beyond the basics, diving deep into real-world applications and strategic insights that elevate the team's data-handling capabilities.

Our virtual/onsite Google BigQuery training offers a tailor-made experience, fitting seamlessly into the organization's schedule while delivering an impactful hands-on learning experience. 

Key Skills Employees Gain from Google BigQuery Training

Google BigQuery skills corporate training will enable teams to effectively apply their learnings at work.

  • Data Transformation
  • Query Optimization
  • Data Modeling
  • Security & Access Control
  • Advanced Querying Techniques
  • Advanced Querying Techniques

Key Learning Outcomes of Google BigQuery Training Workshop

Edstellar’s Google BigQuery group training will not only help your teams to acquire fundamental skills but also attain invaluable learning outcomes, enhancing their proficiency and enabling application of knowledge in a professional environment. By completing our Google BigQuery workshop, teams will to master essential Google BigQuery and also focus on introducing key concepts and principles related to Google BigQuery at work.


Employees who complete Google BigQuery training will be able to:

  • Interpret and visualize query results using data visualization tools
  • Utilize Google BigQuery's features for data transformation, filtering, and aggregation
  • Optimize query performance and resource utilization to enhance data processing efficiency
  • Apply data modeling principles to design efficient and scalable Google BigQuery solutions
  • Implement security and access controls in Google BigQuery to ensure data privacy and governance
  • Apply advanced querying techniques in Google BigQuery to extract relevant information from complex datasets

Key Benefits of the Google BigQuery Group Training

Attending our Google BigQuery classes tailored for corporations offers numerous advantages. Through our Google BigQuery group training classes, participants will gain confidence and comprehensive insights, enhance their skills, and gain a deeper understanding of Google BigQuery.

  • Nurtures advanced skills in writing and optimizing SQL queries, ensuring efficient data retrieval and analysis
  • Fosters the ability to implement cost-effective data strategies, optimizing resource utilization and reducing overheads
  • Enhances understanding of data integration and management, facilitating seamless data flow across various platforms
  • Develops proficiency in using BigQuery ML for machine learning applications, fostering innovation in data-driven insights
  • Empowers employees with the ability to leverage BigQuery’s serverless architecture for scalable data warehousing solutions
  • Equips the team with expertise in handling large-scale data analysis using Google BigQuery, enhancing data processing capabilities

Topics and Outline of Google BigQuery Training

Our virtual and on-premise Google BigQuery training curriculum is divided into multiple modules designed by industry experts. This Google BigQuery training for organizations provides an interactive learning experience focused on the dynamic demands of the field, making it relevant and practical.

  1. Getting started with BigQuery
    • Understanding the BigQuery interface
    • Executing basic queries
    • Accessing query history and saved queries
  2. Navigating the BigQuery UI
    • Using the query editor
    • Exploring the job panel
    • Managing BigQuery datasets
  3. Advanced UI features
    • Utilizing keyboard shortcuts
    • Customizing the UI layout
    • Saving and sharing queries
  1. Understanding BigQuery jobs
    • Identifying different job types
    • Job priorities and impact
    • Viewing job history
  2. Job management techniques
    • Cancelling and retrying jobs
    • Setting job labels for the organization
    • Debugging common job errors
  3. Automating and scheduling jobs
    • Creating scheduled queries
    • Using Cron jobs with BigQuery
    • Monitoring scheduled job executions
  1. Creating and configuring datasets
    • Defining a new dataset
    • Setting dataset permissions
    • Configuring dataset options
  2. Managing dataset lifecycle
    • Updating dataset descriptions
    • Copying and transferring datasets
    • Setting dataset expiration
  3. Securing datasets
    • Understanding IAM roles for datasets
    • Applying dataset access controls
    • Best practices for dataset security
  1. Understanding table schemas
    • Schema structure and data types
    • Auto-detect vs. manual schema definition
    • Schema evolution strategies
  2. Modifying table schemas
    • Adding and removing fields
    • Changing field data types
    • Handling schema mismatches during data loading
  3. Schema management best practices
    • Schema versioning and management
    • Utilizing schema enforcement
    • Leveraging schema description for documentation
  1. Table operations and management
    • Creating tables in BigQuery
    • Cloning and copying tables
    • Deleting tables from datasets
  2. Data manipulation in tables
    • Inserting data into tables
    • Updating and patching table data
    • Managing table data lifecycle
  3. Optimizing table performance
    • Understanding table partitioning
    • Implementing table clustering
    • Analyzing table performance and storage
  1. Introduction to partitioned tables
    • Benefits of partitioning in BigQuery
    • Types of partitioned tables
    • Creating partitioned tables
  2. Managing partitioned data
    • Querying partitioned tables
    • Updating partitioned tables
    • Maintaining optimal partition strategies
  3. Advanced partitioning techniques
    • Dynamic partitioning in queries
    • Partition expiration and trimming
    • Best practices for partitioned table performance
  1. Fundamentals of clustering
    • The concept of clustering in BigQuery
    • Creating clustered tables
    • Benefits of clustering for performance
  2. Querying clustered tables
    • Writing efficient queries on clustered tables
    • Understanding the impact of clustering on query costs
    • Strategies for clustering key selection
  3. Maintaining clustered tables
    • Monitoring clustered table performance
    • Updating clustering strategies
    • Best practices for clustered table maintenance
  1. Understanding BigQuery views
    • The role of views in BigQuery
    • Creating and using views
    • Managing view permissions
  2. Advanced view functionalities
    • Parameterized views
    • Materialized views for performance optimization
    • Managing view refreshes
  3. Views and access patterns
    • Sharing data through views
    • Controlling data access with view-based filters
    • Using views to simplify complex queries
  1. Introduction to resource labeling
    • Benefits of labeling resources
    • Creating and applying labels to BigQuery resources
    • Labeling best practices for organization
  2. Managing labels
    • Editing and removing labels
    • Filtering resources by labels
    • Label strategies for cost allocation and tracking
  3. Label policies and governance
    • Enforcing label policies
    • Auditing resource labels
    • Labeling for compliance and security management
  1. Data ingestion methods
    • Batch loading vs. streaming data
    • Using the command-line tool and UI for data loading
    • Data formats and loading considerations
  2. Troubleshooting data loading issues
    • Diagnosing common load job errors
    • Validating data before and after loading
    • Ensuring data quality and consistency
  3. Best practices for data loading
    • Optimizing load job performance
    • Incremental data loads for efficiency
    • Security best practices during data ingestion
  1. Writing effective queries
    • Crafting performant SQL queries
    • Utilizing nested and repeated fields
    • Applying advanced SQL functions
  1. Query optimization techniques
    • Understanding and leveraging query execution plans
    • Optimizing for cost and performance
    • Using query cache for repeated query execution
  2. Advanced analytical functions
    • Implementing window functions
    • Using BigQuery ML for predictive analytics
    • Analyzing data with geospatial functions
  1. External data source connections
    • Setting up external data connections
    • Querying data from Google Cloud Storage, Drive, and other sources
    • Performance considerations for external data queries
  2. Federated query execution
    • Writing federated queries across different data sources
    • Caching external query results
    • Best practices for managing external data
  3. Security and compliance with external data
    • Ensuring data encryption and protection
    • Compliance considerations for external data
    • Access controls for federated data sources
  1. Understanding BigQuery pricing
    • Breakdown of BigQuery's cost structure
    • Tools for monitoring and analyzing BigQuery costs
    • Setting up cost alerts and budgets
  2. Cost optimization strategies
    • Reducing data processed with query optimization
    • Managing storage costs effectively
    • Utilizing flat-rate pricing options
  3. Managing cost with resource management
    • Applying quotas and limits on BigQuery usage
    • Optimizing job scheduling for cost efficiency
    • Using cost controls for different project environments
  1. BigQuery security overview
    • Understanding BigQuery's security model
    • Implementing IAM roles and permissions
    • Data encryption at rest and in transit
  2. Data protection and compliance
    • Compliance certifications relevant to BigQuery
    • Best practices for data masking and anonymization
    • Security considerations for shared datasets
  3. Audit and monitoring for security
    • Setting up audit logs for BigQuery events
    • Monitoring access and usage patterns
    • Responding to security incidents in BigQuery
  1. Getting started with the BigQuery API
    • API use cases and scenarios
    • Setting up and authenticating API requests
    • Building and executing API calls
  2. BigQuery API advanced operations
    • Automating dataset and table management
    • Streaming data inserts via the API
    • Extracting data and running asynchronous jobs
  3. API best practices and optimization
    • Handling API rate limits and errors
    • Optimizing API calls for performance
    • Security best practices when using the BigQuery API

Target Audience for Google BigQuery Training Course

The Google BigQuery training program can also be taken by professionals at various levels in the organization.

  • BI Managers
  • Data Engineering Managers
  • Business Intelligence Analysts
  • Data Scientists
  • ETL Developers
  • Database Administrators
  • Cloud Data Managers
  • Data Architects
  • BI Developers
  • Cloud Data Engineers
  • Analytics Engineers
  • Cloud Architects

Prerequisites for Google BigQuery Training

Professionals can take the Google BigQuery training course with a basic understanding of  database concepts and Google Cloud Platform Fundamentals (CP100A) or Google Cloud Platform Big Data. Having experience in using a SQL-like query language to analyze data would be an advantage.

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Corporate Group Training Delivery Modes
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At Edstellar, we understand the importance of impactful and engaging training for employees. To ensure the training is more interactive, we offer Face-to-Face onsite/in-house or virtual/online for companies. This approach has proven to be effective, outcome-oriented, and produces a well-rounded training experience for your teams.

 Virtual trainig

Our virtual group training sessions bring expert-led, high-quality training to your teams anywhere, ensuring consistency and seamless integration into their schedules.

With global reach, your employees can get trained from various locations
The consistent training quality ensures uniform learning outcomes
Participants can attend training in their own space without the need for traveling
Organizations can scale learning by accommodating large groups of participants
Interactive tools can be used to enhance learning engagement
 On-site trainig

Edstellar's onsite group training delivers immersive and insightful learning experiences right in the comfort of your office.

Higher engagement and better learning experience through face-to-face interaction
Workplace environment can be tailored to learning requirements
Team collaboration and knowledge sharing improves training effectiveness
Demonstration of processes for hands-on learning and better understanding
Participants can get their doubts clarified and gain valuable insights through direct interaction
 Off-site trainig

Edstellar's off-site group training programs offer a unique opportunity for teams to immerse themselves in focused and dynamic learning environments away from their usual workplace distractions.

Distraction-free environment improves learning engagement
Team bonding can be improved through activities
Dedicated schedule for training away from office set up can improve learning effectiveness
Boosts employee morale and reflects organization's commitment to employee development

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Google BigQuery Corporate Training

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        Get Your Team Members Recognized with Edstellar’s Course Certificate

        Upon successful completion of the Google BigQuery training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development.

        This certificate validates the employee's acquired skills and is a powerful motivator, inspiring them to enhance their expertise further and contribute effectively to organizational success.

        Course Completion Certificate

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        The instructor-led training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Access practices.

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