Partitioning and Clustering BigQuery | Scribe

    Partitioning and Clustering BigQuery

    • Hafeez Baig |
    • 10 steps |
    • 52 seconds
    1
    Sign into the **Google Cloud Console**
    2
    Type "**BigQuery**" in the search bar and click on the **BigQuery** option
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    **What is BigQuery?**\ \ **BigQuery** is a fully-managed, serverless data warehouse offered by Google Cloud. It enables fast, SQL-based analysis of large datasets. BigQuery is designed for scalable querying, allowing users to process petabytes of data quickly with built-in machine learning and geospatial analysis features. It's widely used for analytics, business intelligence, and data science applications due to its speed, scalability, and ease of integration with other Google Cloud services.
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    **Explorer** wizard will open, click on the **BigQuery Studio** from the left bar
    4
    Click on the **ADD** button
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    On the right side **Add** wizard will open, here you can view the sources for the Big Query
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    Click on the **Data transfers** option from the left bar, here you can create a Transfer for Data Transfer
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    **What are Data transfers?**\ \ In Google Cloud, **data transfers** refer to the process of moving data into Google Cloud services, like BigQuery or Cloud Storage, from various external sources such as SaaS applications, databases, or other cloud services. The **BigQuery Data Transfer Service** automates data loading from these sources into BigQuery on a scheduled basis.
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    Click on the **Scheduled queries** option from the left bar, here you can create Scheduled Query in Editor
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    **What are Scheduled queries?**\ \ **Scheduled queries** in Google BigQuery allow you to automate running SQL queries at regular intervals. You can set a schedule (daily, weekly, etc.) for your queries to execute, and the results are automatically saved to a specified table. This feature is useful for generating reports, updating datasets, or performing routine data analysis without manual intervention.
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    Click on the **Analytics Hub** option from the left bar, here you can create an Exchange and Clean Room for Analytics
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    **What is Analytics Hub?**\ \ **Analytics Hub** is a Google Cloud service that allows organizations to securely share and exchange data and insights at scale. It enables data providers to publish datasets, and data consumers to subscribe to and access these datasets from a centralized platform. Analytics Hub is built on BigQuery, making it easy to share structured data for analytics while maintaining control over data security and privacy.
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    Click on the **Dataform** option from the left bar, here you can create a Repository
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    **What is Dataform?**\ \ **Dataform** is a Google Cloud tool designed to help teams manage data workflows in BigQuery. It simplifies the process of transforming raw data into analytics-ready datasets by enabling users to create and manage SQL-based data pipelines. Dataform allows for version control, collaboration, and automation of data transformation tasks, making it easier to maintain and scale data processes. It's particularly useful for building complex data transformations in an organized and repeatable way.
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    Click on the **Partner Center** option from the left bar, here you can explore tools and services for your workflow
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    **What is Partner Center?**\ \ **Partner Center** is a Google Cloud platform that allows Google Cloud partners to manage their relationship with Google, including tracking their performance, managing customer accounts, and accessing partner-specific resources. It provides tools for partners to view analytics, manage deals, and access support and training materials to better serve their clients and grow their business.
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    Congratulations! on completing this lab and Understanding Partitioning and Clustering BigQuery