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Drive Team Excellence with Google BigQuery Corporate Training

Empower your teams with expert-led on-site, off-site, and virtual Google BigQuery Training through Edstellar, a premier corporate training provider for organizations globally. Designed to meet your specific training needs, this group training program ensures your team is primed to drive your business goals. Help your employees build lasting capabilities that translate into real performance gains.

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. 

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Key Skills Employees Gain from instructor-led Google BigQuery Training

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

  • Data Transformation
    Data Transformation is the process of converting data from one format or structure to another. This skill is important for data analysts and engineers to ensure accurate analysis and integration.
  • Query Optimization
    Query Optimization is the process of improving database query performance by refining SQL statements. This skill is important for database administrators and data analysts to ensure efficient data retrieval, reduce load times, and enhance overall system performance.
  • Data Modeling
    Data Modeling is the process of creating visual representations of data structures and relationships. This skill is important for data analysts and database developers to ensure accurate data management and analysis.
  • Security & Access Control
    Security & Access Control involves managing and regulating access to physical and digital resources. This skill is important for safeguarding sensitive information and ensuring compliance in roles like IT security, facilities management, and data protection.
  • Advanced Querying Techniques
    Advanced Querying Techniques involve crafting complex database queries to extract, manipulate, and analyze data efficiently. this skill is important for data analysts and database administrators, as it enhances data-driven decision-making and optimizes performance.
  • Advanced Querying Techniques
    Advanced Querying Techniques involve crafting complex database queries to extract, manipulate, and analyze data efficiently. this skill is important for data analysts and database administrators, as it enhances data-driven decision-making and optimizes performance.

Key Learning Outcomes of Google BigQuery Training Workshop for Employees

Upon completing Edstellar’s Google BigQuery workshop, employees will gain valuable, job-relevant insights and develop the confidence to apply their learning effectively in the professional environment.

  • 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 with Instructor-led Face to Face and Virtual Options

Attending our Google BigQuery group training classes provides your team with a powerful opportunity to build skills, boost confidence, and develop a deeper understanding of the concepts that matter most. The collaborative learning environment fosters knowledge sharing and enables employees to translate insights into actionable work outcomes.

  • 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 structured into focused modules developed by industry experts. This training for organizations provides an interactive learning experience that addresses the evolving demands of the workplace, making it both 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

Who Can Take the 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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Delivering Training for Organizations across 100 Countries and 10+ Languages

Corporate Group Training Delivery Modes
 for Google BigQuery Training

At Edstellar, we understand the importance of impactful and engaging training for employees. As a leading Google BigQuery training provider, we ensure the training is more interactive by offering Face-to-Face onsite/in-house or virtual/online sessions for companies. This approach has proven to be effective, outcome-oriented, and produces a well-rounded training experience for your teams.

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Face to Face Instructor-led Training
Virtual Google BigQuery Training

Edstellar's Google BigQuery virtual/online 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
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On-site Google BigQuery Training

Edstellar's Google BigQuery inhouse face to face instructor-led 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
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Off-site Google BigQuery Training

Edstellar's Google BigQuery offsite face-to-face instructor-led group training 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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        Edstellar: Your Go-to Google BigQuery Training Company

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        "The Google BigQuery training exceeded my expectations in every way. As a Senior Software Engineer, I gained comprehensive knowledge of advanced methodologies that transformed my approach to strategic practical and immediately applicable. I've confidently led multiple high-visibility initiatives leveraging this comprehensive knowledge. The instructor's expertise in practical simulations made complex concepts crystal clear and actionable.”

        Ferdinand Chandler

        Senior Software Engineer,

        Digital Innovation Platform

        "This Google BigQuery course equipped me with comprehensive strategic frameworks expertise that I've seamlessly integrated into our professional services practice. The hands-on modules covering real-world case studies and confidently design solutions that consistently deliver measurable business results. Our project success rate and profitability increased dramatically within the quarter, validating the immediate impact of this training program.”

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        Global Technology Solutions Provider

        "The Google BigQuery training transformed our team's entire approach to technical mastery management and execution. As a Senior Software Engineer, the extensive coverage of practical applications, hands-on exercises, and proven concepts to strategic initiatives. Our department achieved a remarkable 50% improvement in operational efficiency metrics. Our team's productivity and solution quality have improved measurably, validating this investment.”

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        “Edstellar’s IT & Technical training programs have been instrumental in strengthening our engineering teams and building future-ready capabilities. The hands-on approach, practical cloud scenarios, and expert guidance helped our teams improve technical depth, problem-solving skills, and execution across multiple projects. We’re excited to extend more of these impactful programs to other business units.”

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