Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
12 Hour(s) 9 Minute(s)
Language
English
Rating
Course Overview
Become an Analytics Engineer expert with just ONE course. Learn Data Modelling, dbt, Google Bigquery & many more!
Welcome 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 (Data build tool) & 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
RECENT UPDATES:
Mar2023 - Updated Glossary and added more contents
Mar2024 - New: dbt Power User accelerated development lectures (Including usage of Data Pilot, Generative AI driven workflow assistant)
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
Course Content
- 11 section(s)
- 150 lecture(s)
- Section 1 Introduction
- Section 2 What is a database?
- Section 3 What is a data warehouse?
- Section 4 Data Modelling & ERD Notations
- Section 5 Normalisation & Denormalisation
- Section 6 Data Warehouse Design Methodologies
- Section 7 Dimensional Modelling
- Section 8 Setting up Environments
- Section 9 (Hands-on dbt) Building dimensional data warehouse
- Section 10 Accelerate dbt Development with Power User for dbt (DataPilot)
- Section 11 Glossary
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
Reviews
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PPravin Kadam
Thnank you
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KKatlego Motaung
Clear-cut and visual explanations make the content an easy digest!
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JJosh Bailey
Good insightful course, very theory heavy at first & hands on section requires some patience to setup.
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BBoules Emad Boules
too much theory, without trying to clarify, or simplify concepts. just reading slides bullet points. - the slides are not sharable, nor the dataflow diagram. - however comprehensive and encapsulates everything in one courese.
