Data Build Tool Course Content

This DBT ETL training online program consists of all DBT core and DBT Cloud modules arranged sequentially to deliver end-to-end data transformation skills. This training focuses on the DBT cloud version and covers critical components such as DBT architecture, features, analyses, seeds, models, macros, snapshots, tests, materializations, jinja templates, hooks, integrations, etc. Below are the Data Build Tool DBT training modules covered during this program:

Topics:

  • Traditional Data Teams
  • Analytics Engineer
  • ETL vs ELT
  • Overview of Modern Data Stack
  • Learn DBT

Topics:

  • DBT Features
  • DBT Maturity Model
  • Data Platforms
  • Version Control
  • DBT Cloud Configuration
  • Version Control
  • DBT Cloud UI
  • What is Data Build Tool

Topics:

  • Data Modeling Overview
  • Modularity
  • Data Model Building Process
  • Ref Functions
  • Data Modeling History
  • Naming Conventions

Lab:

  • Writing Models
  • Interpolating a schema using ref()

Topics:

  • Defining Data Sources
  • Source Configuration
  • Source Freshness

Lab:

  • Assigning Sources
  • Configuration of source freshness
  • Writing Models

Topics:

  • Testing in DBT?
  • Why Testing is Required?
  • Testing Sources
  • Types of Tests

Lab:

  • Adding Tests to a Project
  • Executing a custom data test
  • Writing a schema test

Topics:

  • Traditional Data Teams
  • Analytics Engineer
  • ETL vs ELT
  • Overview of Modern Data Stack
  • Learn DBT

Topics:

  • DBT Features
  • DBT Maturity Model
  • Data Platforms
  • Version Control
  • DBT Cloud Configuration
  • Version Control
  • DBT Cloud UI
  • What is Data Build Tool

Topics:

  • Data Modeling Overview
  • Modularity
  • Data Model Building Process
  • Ref Functions
  • Data Modeling History
  • Naming Conventions

Lab:

  • Writing Models
  • Interpolating a schema using ref()

Topics:

  • Defining Data Sources
  • Source Configuration
  • Source Freshness

Lab:

  • Assigning Sources
  • Configuration of source freshness
  • Writing Models

Topics:

  • Testing in DBT?
  • Why Testing is Required?
  • Testing Sources
  • Types of Tests

Lab:

  • Adding Tests to a Project
  • Executing a custom data test
  • Writing a schema test

Topics:

  • What is Documentation in DBT?
  • Documentation Importance
  • Documentation & Doc Blocks
  • Source Documenting

Topics:

  • Deployment Considerations
  • Configuring the DBT Cloud job
  • CFU - Deployment

Topics:

  • Fundamentals of Jinja
  • Jinja Applications
  • Best Practices
  • Advanced Jinja’s

Topics:

  • Define Macros
  • Dev Macro
  • Dry Code & Readability
  • Advanced Macros

Topics:

  • Need of Packages
  • Installing packages
  • Packages with Models
  • Packages With Macros

Topics:

  • Basics of Materialization
  • Incremental Models
  • Tables & Views
  • Ephemeral Models
  • Snapshots & Implementation
  • Incremental Models

Topics:

  • Analyses Fundamentals
  • Analyses Implementation
  • Seeds & Implementation

Lab:

  • Fixing Seds
  • Seed files for filtering

Concepts:

Lab:

  • Configuring a Snapshot of a source
  • Configuring a Snapshot to a Table

Topics:

  • Migrating Code
  • Translating Code
  • Cosmotec Cleanups
  • Staging Models

Topics:

  • Overview Incremental Models
  • Incremental Load Configuration
  • Work with incremental models

Topics:

  • DBT Environment
  • Configuring DBT for zero-copy clones
  • Pull request handling
  • Continuous Integration
  • Scheduled Runs
  • DBT Core
  • DBT Data

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LIVE SESSIONS


  • Real-time Trainers
  • Live interactive Sessions
  • Cloud Labs

CORPORATE TRAINING


  • Customized Training Solutions
  • Blended Delivery Model
  • Project Implementation Support

SELF-PACED LEARNING


  • High-Quality Videos
  • Access to Materials
  • Permanent Access

Data Build Tool (DBT) Course Objectives

Following are the core skills you will gain during this DBT online training:

  • DBT Fundamentals
  • DBT Architecture
  • ETL & ELT
  • Data Warehouse Configuration
  • DBT Installation
  • Connecting With Sources
  • Project Flow
  • Models in DBT
  • Materialization
  • Models Integration
  • Seeds & Sources
  • Source Integration & Freshness
  • Slowly Changing Dimensions
  • Analyses and Hooks
  • Macros
  • Documentation
  • DBT Core vs DBT Cloud
  • DBT Analytics Engineering Certification Guidance
  • Data Build Tool Interview Preparation
     

You should have a good understanding of SQL, ETL, ELT, and Data warehousing concepts.

Following are the individuals who can enroll in our DBT ETL training Online:

  • ETL Professionals
  • Data Warehouse Professionals
  • Data Analysts
  • Data Visualization Professionals
  • Data Engeenering Professionals

Data Engineering is one of the leading technologies in today's IT world. Data has become a new resource for modern businesses, enabling companies to make more reliable decisions. A modern data stack requires multiple tools to make data engineering successful. DBT is one significant technology being used in modern data engineering.

DBT is an open-source platform that helps organizations simplify the data transformation process in their data warehouse with simple SQL queries. It comes with rich features to transform data effectively and produce reliable data that can be used for various business operations.

The usage of the Data Build tool has been growing tremendously over the years and demand for Skilled DBT professionals is increasing. There are very limited professionals in the market who are skilled in DBT.

Our DBT training has been designed to impart the learners with core DBT skills such as DBT fundamentals, Jnja’s, Macros, Data modeling, integrations, materializations, and more. This program is more practical-oriented and helps you gain data transformation skills.

The following are the core components of Data Build Tool Certification :

  • Compiler
  • Jinja
  • Jinja Extensions
  • Package Manager
  • Runner

Below mentioned are the notable benefits of DBT Tool :

  • Need not use boilerplate code
  • Easy to control For Loops, uses Macros to share repeated queries
  • Ref function offers complete control
  • Snapshot Facility of Raw data
  • Auto-generated documentation
  • Version control

Basically, data engineering teams use a data-build tool. Basically, organizations that have multiple data sources and need a centralized place to transform data use DBT. Below listed are the common roles that use the DBT platform:

  • Data Engineers
  • Data Analysts
  • Data Scientists
  • ETL Developers

DBT offers two modules which are the DBT Core and DBT Cloud
DBT Core is an open-source platform and no cost is associated with it.  Whereas DBT Cloud is an enterprise-grade solution and is available on a subscription basis.

DBT Cloud is a browser-based platform that allows developers to build, test, schedule, and troubleshoot data models. It also provides DBT cloud CLI, which can be used to develop data models. DBT Cloud offers a robust environment for developers and extended features compared to DBT Core.

The following are the DBT Cloud Features:

  • DBT Cloud CLI
  • DBT Cloud IDE
  • Schedule & Run DBT Jobs
  • Monitoring and Alerting
  • API Integration
  • Run Visibility
  • DBT Semantic Layer
  • Host & Share Documentation
  • Security

A data build Tool (DBT) is a data processing framework that performs T in ETL (Extract, Transform, and Load). DBT uses cloud data platforms like Snowflake to perform data transformation, cleaning, and aggregation tasks. It is built on Python and has adapters to integrate with databases & query engines.

A seed is a CSV file in DBT residing in the seeds directory that can be loaded to a data warehouse like Snowflake using the Seed Command. Seeds can handle static data (data that doesn't change frequently) and smaller data sets like country lists, date dimension tables, etc.

The DBT “Model” is a clear plan to transform a raw dataset into a reusable one. A model also contains information about transformations that can be performed on raw data.

Data Build Tool Certification

This data build tool training course is designed to provide you with the end-to-end knowledge required to clear DBT Analytics Engineering Certification exams and get certified. In addition to training, participants will receive certification dumps and guidance. They are also offered a course completion certificate.

Data Build tool is one of the most powerful SQL-based data transformation tools and adopted by 20,000+ organizations across the globe. We know how important data analytics have become and DBT plays a major role in data analytics.

DBT Analytics Engineering certification will make you stand out from your peers and demonstrates your skills & ability to handle DBT projects.

Following are the 2 Data Build Tool Certifications:

  • Dbt Analytics Engineering Certification Exam
  • Dbt Cloud Administrator Certification Exam

The Analytics Engineering Certification Exam is been designed to validate candidates' knowledge in building, testing, and maintaining Data models. Also, test the candidate's ability in applying data engineering principles and enabling data accessibility to all.

Exam details:

Number of Questions - 65

Duration -  120 Minutes

Cost - $ 200

Passing Score: 65%

The Dbt Cloud Administrator Certification Exam has been designed to test the candidates' level of knowledge in the below areas:

  • DBT Cloud Configuration
  • Troubleshooting Issues
  • Managing DBT Cloud connections
  • Managing DBT Environment

Exam details:

Number of Questions - 65

Duration -  120 Minutes

Cost - $ 200

Passing Score: 63%

techsolidity-certification

Data Build Tool Projects

Practical experience is very essential to gain the confidence required to get into your next project. With an aim to deliver practical transformation skills, we have designed this Data Build tool training around two live projects. Following are the projects that you are going to work on during this training.

DBT Training Reviews

DBT FAQ's

DBT does not perform all the ETL tasks, such as extracting, transforming, and loading, but it is good at transforming data in the data warehouse. DBT is like the ELT process (extract, load, and change). It performs the last role (transformation) in ELT.

The DBT platform was developed using Python and generally uses SQL for data transformation operations. As the demand for multi-language support has grown, DBT has worked hard to support building Python models. Now, DBT also supports Python to build models.

DBT Cloud has become so popular because it makes data modeling simple and data engineer life easier by eliminating hard coding. Moreover, one can test all data models and sources without depending on external tools. You can use basic SQL queries to write transformation queries or you can also use jinja language. Overall it is very easy to learn the data build Tool (DBT). This DBT Cloud training has been designed from scratch and covers advanced concepts. 

Generally, DBT offers two versions which are DBT Core and DBT Cloud. DBT offers responsive UI and easy to navigate through different tabs. It will be hosted on a powerful cloud platform to give optimal performance and required speed. DBT Cloud also offers additional features such as a DBT job scheduler, metadata, IDE, observability, integrations with other tools, etc. 

You don't have to worry if you are unfamiliar with other programming languages. You can still use SQL select statements to write custom transformations. It makes the work of data engineers who don’t have work experience in multiple languages easier.

Yes, Techsolidty offers you two types of Discounts: one is a group discount and the other is a referral discount. Join as a group in this Data  Build  Tool Training to grab a discount. 

Yes, In order to provide you the financial flexibility, we provide you the chance to pay the DBT Cloud Training fee in two installments.

Due to any reasons, you would like to cancel your registration after paying the fee, you should intimate the same to us within the first two classes. The refund amount will be processed within 30 days from the requested date.
 

To meet customer expectations, we provide multiple types of DBT ETL Training, which include Live instructor-led training, Self-paced training, blended training, classroom training, corporate training, etc.

Yes, our Data build tool training Contains two live projects! You will be using each component during DBT cloud training to gain practical exposure.