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Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console. Data validation is a critical step in data warehouse, database, or data lake migration.

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This is a self-paced lab that takes place in the Google Cloud console. Data validation is a critical step in data warehouse, database, or data lake migration.

DVT prints results in the command line interface by default, but can also write results to BigQuery. It is recommended to use BigQuery as a report handler to store and analyze the output.

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What's inside

Syllabus

Automate Validation using the Data Validation Tool (DVT)

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Applicable to data warehouses, databases, and data lake migration
Teaches DVT skills which are core to data validation
Taught by Google Cloud Training which is recognized for its expertise in data validation
Self-paced, hands-on lab format enhances learning through practical application
Leverages BigQuery for report handling, aligning with industry best practices
Covers automating validation with DVT, a widely used tool in the data validation field

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Automate Validation using the Data Validation Tool (DVT) with these activities:
Review basic data management concepts
Review basic data management concepts to strengthen your foundation for understanding data validation.
Browse courses on Data Management
Show steps
  • Review your notes or textbooks on data management.
  • Take a practice quiz or complete some exercises on data management concepts.
  • Discuss data management concepts with a classmate or colleague.
Organize and review course materials
Organize and review course materials to ensure you have a solid understanding of the fundamentals of data validation.
Show steps
  • Gather all course materials, including lecture notes, readings, and assignments.
  • Organize the materials into a logical structure.
  • Review the materials regularly to reinforce your understanding.
Participate in a study group
Join a study group to discuss course material, share insights, and support each other's learning.
Show steps
  • Find other students enrolled in the course.
  • Schedule regular meetings with the group.
  • Review course material and discuss concepts.
  • Work on assignments and projects together.
Five other activities
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Show all eight activities
Write a blog post or article about DVT
Create a blog post or article about DVT to share your knowledge and insights with others.
Show steps
  • Choose a topic and develop an outline.
  • Research and gather information about your topic.
  • Write the first draft of your article.
  • Edit and revise your article.
  • Publish your article on a blog or website.
Practice data validation scenarios
Practice different data validation scenarios to reinforce the concepts and techniques covered in the course.
Browse courses on Data Validation
Show steps
  • Set up a test environment with sample data.
  • Create a series of data validation rules.
  • Execute the rules against the sample data.
  • Analyze the results and identify any errors or inconsistencies.
  • Iterate and refine the rules until they are accurate and comprehensive.
Participate in a data validation challenge
Participate in a data validation challenge to test your skills and learn from others.
Show steps
  • Find a data validation challenge that aligns with your interests.
  • Prepare for the challenge by practicing and reviewing relevant concepts.
  • Participate in the challenge and submit your solution.
  • Review the results and identify areas for improvement.
Explore advanced DVT techniques
Review advanced DVT techniques to enhance your skills and knowledge.
Browse courses on Data Validation
Show steps
  • Find and review online tutorials on advanced DVT techniques.
  • Follow the tutorials and practice implementing the techniques.
  • Apply the techniques to real-world scenarios.
  • Share your findings and experiences with others.
Build a data validation pipeline
Create a data validation pipeline to automate the validation process and ensure data integrity in a production environment.
Browse courses on Data Warehouse
Show steps
  • Design the pipeline architecture.
  • Implement the data validation rules.
  • Integrate the pipeline with your data processing system.
  • Test and deploy the pipeline.
  • Monitor the pipeline and make adjustments as needed.

Career center

Learners who complete Automate Validation using the Data Validation Tool (DVT) will develop knowledge and skills that may be useful to these careers:
Data Validation Engineer
Data Validation Engineers are responsible for developing and implementing data validation solutions. They work with data analysts and business stakeholders to understand data requirements, and develop and implement data validation solutions. This course may be particularly helpful for Data Validation Engineers by providing them with the skills and knowledge needed to use DVT to solve complex data validation challenges.
Data Quality Analyst
Data Quality Analysts are responsible for ensuring that data is accurate, complete, and consistent. They work with data analysts and business stakeholders to understand data requirements, and develop and implement data quality solutions. This course may be helpful for Data Quality Analysts by providing them with the skills and knowledge needed to use DVT to identify and resolve data quality issues.
Data Architect
Data Architects are responsible for designing and developing data architectures. They work with data analysts and business stakeholders to understand data requirements, and develop and implement data architecture solutions. This course may be helpful for Data Architects by providing them with the skills and knowledge needed to use DVT to validate data before it is used to develop data architectures.
Data Analyst
Data Analysts are responsible for analyzing data to identify trends and patterns. They work with business stakeholders to understand data requirements, and develop and implement data analysis solutions. This course may be helpful for Data Analysts by providing them with the skills and knowledge needed to use DVT to validate data before it is analyzed.
Database Administrator
Database Administrators are responsible for managing and maintaining databases. They work with database developers to design, implement, and optimize databases, and they ensure that databases are running smoothly and efficiently. This course may be helpful for Database Administrators by providing them with the skills and knowledge needed to use DVT to validate data in databases.
Data Scientist
Data Scientists are responsible for developing and implementing data science solutions. They work with data analysts and business stakeholders to understand data requirements, and develop and implement data science models. This course may be helpful for Data Scientists by providing them with the skills and knowledge needed to use DVT to validate data before it is used to train data science models.
Data Warehouse Engineer
Data Warehouse Engineers are responsible for designing, building, and maintaining data warehouses. They work with data analysts and business intelligence professionals to understand data requirements, and develop and implement data warehouse solutions. This course may be helpful for Data Warehouse Engineers by providing them with the skills and knowledge needed to use the Data Validation Tool (DVT) to validate data in data warehouses.
Business Intelligence Analyst
Business Intelligence Analysts are responsible for analyzing data to identify trends and patterns. They work with business stakeholders to understand data requirements, and develop and implement business intelligence solutions. This course may be helpful for Business Intelligence Analysts by providing them with the skills and knowledge needed to use DVT to validate data before it is used to develop business intelligence solutions.
Data Engineer
Data Engineers are responsible for building and maintaining data pipelines. They work with data scientists and business stakeholders to understand data requirements, and develop and implement data engineering solutions. This course may be helpful for Data Engineers by providing them with the skills and knowledge needed to use DVT to validate data before it is used to build data pipelines.
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and implementing machine learning solutions. They work with data scientists and business stakeholders to understand data requirements, and develop and implement machine learning models. This course may be helpful for Machine Learning Engineers by providing them with the skills and knowledge needed to use DVT to validate data before it is used to train machine learning models.
Database Developer
Database Developers are responsible for designing and developing databases. They work with database administrators and business stakeholders to understand data requirements, and develop and implement database solutions. This course may be helpful for Database Developers by providing them with the skills and knowledge needed to use DVT to validate data before it is loaded into databases.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. They work with software architects and business stakeholders to understand software requirements, and develop and implement software solutions. This course may be helpful for Software Engineers by providing them with the skills and knowledge needed to use DVT to validate data before it is used to develop software applications.
Technical Writer
Technical Writers are responsible for writing technical documentation. They work with engineers, developers, and other technical professionals to understand technical concepts, and develop and write technical documentation. This course may be helpful for Technical Writers by providing them with the skills and knowledge needed to write documentation about DVT and data validation.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Automate Validation using the Data Validation Tool (DVT).
Offers a practical approach to data validation, providing step-by-step guidance on implementing data validation solutions in real-world scenarios. It covers a wide range of data validation techniques and challenges.
Provides a comprehensive overview of data validation techniques and strategies. It covers both theoretical concepts and practical applications, making it a useful resource for anyone involved in data management or analysis.
Provides a practical guide to big data analytics, including techniques for data validation and quality control. It valuable resource for anyone who wants to learn more about how to use big data to solve business problems.
Classic reference on data warehousing, including chapters on data validation and quality control. It valuable resource for anyone who wants to learn more about the design and implementation of data warehouses.
Provides a practical guide to data integration, including techniques for data validation and quality control. It valuable resource for anyone who wants to learn more about how to integrate data from different sources.
Comprehensive textbook on data mining, including chapters on data validation and quality control. It valuable resource for anyone who wants to learn more about the techniques used to extract knowledge from data.
Comprehensive textbook on deep learning, including chapters on data validation and quality control. It valuable resource for anyone who wants to learn more about the techniques used to train and evaluate deep learning models.
Comprehensive textbook on reinforcement learning, including chapters on data validation and quality control. It valuable resource for anyone who wants to learn more about the techniques used to train and evaluate reinforcement learning agents.
Comprehensive textbook on natural language processing, including chapters on data validation and quality control. It valuable resource for anyone who wants to learn more about the techniques used to process and analyze natural language text.
Comprehensive textbook on computer vision, including chapters on data validation and quality control. It valuable resource for anyone who wants to learn more about the techniques used to process and analyze images and videos.

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