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DBT Training in Hyderabad | Data Build Tool Training Online Course

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Visualpath offers the Best DBT (Data Build Tool) online training course by real-time experts for hands-on learning. Our DBT (Data Build Tool) training is available in Hyderabad and is provided to individuals globally in the USA, UK, Canada, Dubai, and Australia. Contact us at +91-9989971070. Join us on WhatsApp: Visit: Read Our blog: – PowerPoint PPT presentation

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Date added: 14 August 2024
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Title: DBT Training in Hyderabad | Data Build Tool Training Online Course


1
What Is DBT? An Intro to Transforming Data with
Ease
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2
Overview of DBT
  • DBT is a command-line tool designed to handle the
    transformation stage in a modern data stack.
  • It focuses on transforming data after it's been
    extracted and loaded into a data warehouse (the
    T in ELT).
  • DBT allows data teams to model, test, and
    document their data with simple SQL.
  • Traditional ETL (Extract, Transform, Load) tools
    often combine extraction, transformation, and
    loading processes, which can be complex and hard
    to manage.

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3
Key Features of DBT
  • SQL-Driven Transformation
  • DBT is SQL-based, meaning users can define data
    transformations using SQL queries.
  • This makes it accessible to data analysts,
    engineers, and anyone familiar with SQL.

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4
Version Control and Collaboration
  • DBT integrates seamlessly with Git, allowing
    teams to version control their transformation
    code.
  • Collaboration on data models becomes easier, as
    multiple team members can work on different parts
    of the data pipeline.
  • DBT encourages modularity by breaking down
    transformations into reusable pieces called
    "models."
  • Each model represents a step in the
    transformation process, making pipelines easier
    to debug and maintain.

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5
Data Lineage Tracking
  • DBT provides visibility into the data flow by
    showing how different models are connected,
    ensuring data lineage is transparent and
    traceable.
  • Automated Testing DBT allows users to write
    tests for their data models to ensure data
    integrity.
  • Built-in testing frameworks help catch issues
    early in the transformation process.
  • Documentation DBT generates documentation
    automatically, providing clear insights into what
    each data model does. This makes it easier for
    teams to maintain and onboard new members.

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6
How DBT Fits in the Data Pipeline
  • Extract and Load (EL) First, Then Transform (T)
    DBT works after data has been extracted from its
    source and loaded into a data warehouse, making
    it part of an ELT (Extract, Load, Transform)
    process.
  • With data already loaded in the warehouse, DBT
    focuses on transforming it into a structured,
    analytical form.
  • Data Warehouses Supported by DBT DBT integrates
    with popular cloud data warehouses like
    Snowflake, BigQuery, Redshift, and Databricks.
  • The data transformation queries written in DBT
    are executed directly in the data warehouse,
    leveraging the warehouses processing power.

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7
Advantages of Using DBT
  • Simplicity and Scalability With DBT,
    transformation logic is written in SQL, making it
    easy to write and understand.
  • The modular approach makes DBT scalable, allowing
    users to build on top of existing models and
    pipelines.
  • Separation of Concerns By focusing solely on
    the transformation step, DBT allows for a clean
    separation of concerns in the data pipeline.
  • This specialization helps teams optimize each
    part of the data process without overlap.

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8
Increased Collaboration
  • DBT fosters collaboration between data engineers
    and analysts by creating a shared transformation
    layer.
  • Everyone can contribute to and improve the
    models, leading to better data management and
    insights.
  • Data Quality Assurance The ability to run tests
    on models and track the lineage of data ensures
    that the transformed data is accurate, clean, and
    ready for use.

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9
DBT's Ecosystem
  • DBT Core vs. DBT Cloud
  • DBT comes in two main forms DBT Core and DBT
    Cloud.
  • DBT Core Open-source and free to use, providing
    command-line tools for transformation.
  • DBT Cloud A managed service offering with a
    user-friendly interface, job scheduling, and more
    enterprise-grade features.
  • Integration with Analytics and BI Tools DBT
    integrates well with popular BI tools like
    Tableau, Looker, and Mode, allowing seamless
    visualization of transformed data.

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10
Use Cases for DBT
  • Data Transformation in Startups and Enterprises
    DBT is used by organizations of all sizes, from
    small startups to large enterprises.
  • It helps data teams turn raw data into insights
    by standardizing the transformation process.
  • Improving Data Quality for Analytics DBT is
    ideal for teams looking to ensure high data
    quality for analytics or reporting.
  • Its testing framework catches anomalies early in
    the pipeline.

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11
Conclusion
  • DBT is a game-changer in modern data
    transformation. Its SQL-based approach, focus on
    collaboration, modular pipelines, and integration
    with major data warehouses make it an essential
    tool for organizations looking to simplify their
    data workflows.
  • Whether you're a small team or a large
    enterprise, DBT helps ensure that your data
    transformation is efficient, reliable, and
    scalable.

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12
CONTACT
For More Information About Data Build Tool (DBT)
Training Course Address- Flat no 205, 2nd
Floor, Nilgiri
Block, Aditya Enclave,
Ameerpet, Hyderabad-16 Ph. No
91-9989971070 Visit www.visualpath.in
E-Mail online_at_visualpath.in
13
Thank You
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