Rating 4.53 out of 5 (346 ratings in Udemy)
What you'll learn- Learn all the skill sets that is required to become an Analytics Engineer
- In-depth understanding of data modelling techniques
- Ability to participate in architectural decision making and be able to create one
- Data modelling techniques using DBT
- Learn hands-on skills required to build a Data Warehouse from scratch
- Boost your resume with most in-demand Analytics Engineer skills
- Design & Implement a data warehouse
- Create Data …
Rating 4.53 out of 5 (346 ratings in Udemy)
What you'll learn- Learn all the skill sets that is required to become an Analytics Engineer
- In-depth understanding of data modelling techniques
- Ability to participate in architectural decision making and be able to create one
- Data modelling techniques using DBT
- Learn hands-on skills required to build a Data Warehouse from scratch
- Boost your resume with most in-demand Analytics Engineer skills
- Design & Implement a data warehouse
- Create Data Warehouse Architecture
- Design Conceptual, Logical & Physical Models
- Learn various modelling methodologies (Inmon, Kimball, Data Vault, OBT)
- Apply principles of dimensional data modeling in a hands-on
- Learn all the concepts and terms such as the OLTP, OLAP, Facts, Dimensions, Star Schema, Snowflake Schema
DescriptionWelcome to the Analytics Engineering Bootcamp course. the only course you need to become an amazing Analytics Engineer.
This complete Analytics Engineering Bootcamp will take you step-by-step through engaging and fun lectures and teach you everything you need to know on how to succeed as an Analytics Engineer. Throughout this course you’ll get an in depth insight into all the various tools, technologies and modelling concepts.
Students will learn how to design and implement a Data Warehouse solution using DBT & BigQuery.
Each section contains scenario based quiz questions that help solidify key learning objectives for each concept & theory..
By the end of the course, you'll learn and get really good understanding of:
Differences between database and a data warehouse
Concepts between OLTP & OLAP systems
Normalisation & De-Normalisation methods
Data Modelling methodologies such as (Inmon, Kimball, Data Vault & OBT)
Difference between ETL & ELT
Data modelling techniques especially using dbt
Hands-on experience building dimensional data warehouse
Who this course is for:
Data Analyst, BI Analysts or Data Warehouse developers who are looking to become Analytics Engineers or looking to improve existing skills
For data professionals who wants to get a refresher on all the concepts and terms surrounding OLTP & OLAP systems
Students or recent graduates who are looking to get a job as an Analytics Engineer
Anyone who is interested in Analytics Engineer Career Path
