Analytics Engineering for Data Professionals
10 Days
·Cohort-based Course
🔥 Code OFF250 for $250 discount (4 redemptions left)🔥 The course: spin up a modern Data Stack using Snowflake, Fivetran, dbt / SQL, Preset
Analytics Engineering for Data Professionals
10 Days
·Cohort-based Course
🔥 Code OFF250 for $250 discount (4 redemptions left)🔥 The course: spin up a modern Data Stack using Snowflake, Fivetran, dbt / SQL, Preset
Previously at
Course overview
Analytics Engineering is the foundation of Data Science and AI
Analytics Engineering is a dynamic blend of Data Engineering and Data Analytics, serving as the bridge between these two domains. Analytics Engineers develop and maintain a good portion of the data lifecycle, from the ingestion of Data Sources, to the development of Data Warehouses and the corresponding data pipelines, to Business Intelligence tools. Whether you are a Data Analyst/Scientist that would like to practice on modern Data Engineering tools, or an aspiring Analytics Engineer, this workshop is for you.
You will learn how to:
● Start and develop a modern Data Warehouse, using Snowflake.
● Ingest data, on a schedule, from multiple sources, using connectors in Fivetran.
● Clean and transform data, and the basics of ELT (Extract, Load, Transform), using DBT and SQL.
● Spin up and connect a Business Intelligence tool (Preset) to a Data Warehouse.
Who is this course for
01
A Data Analyst or Data Scientist looking to sharpen their Data Engineering skills using modern data tools.
02
A recent graduate looking to land their first Analytics Engineering role with practical skills that are highly marketable.
03
A professional trying to pivot into a Data role and curious about what Analytics Engineering is about.
Key outcomes
Build an end-to-end data engineering product, from raw data to data visualization.
Start and develop a modern Data Warehouse, using Snowflake.
Ingest data, on a schedule, from multiple sources, using connectors in Fivetran.
Clean and transform data using DBT and the universal data language of SQL.
Spin up and connect a Business Intelligence tool (Preset) to a Data Warehouse.
Add this hands-on project to your portfolio, showcasing new marketable skills.
This course includes
5 interactive live sessions
Lifetime access to course materials
8 in-depth lessons
Direct access to instructor
Projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
Analytics Engineering for Data Professionals
Course syllabus
Week 1
Jan
13
Live session 1: Introduction + overview of Data Stack
Mon 1/137:00 PM—8:30 PM (UTC)Jan
14
Live Session 2: Data Warehouse in Snowflake and data ingestion using Fivetran
Tue 1/147:00 PM—8:30 PM (UTC)Jan
16
Live Session 3: Setting up Github and DBT
Thu 1/167:00 PM—8:30 PM (UTC)
Introduction to Analytics Engineering
Ingesting data into a Data Warehouse
Configuring data pipelines in DBT
Week 2
Jan
20
Live Session 4: SQL pipelines in DBT
Mon 1/207:00 PM—8:30 PM (UTC)Jan
22
Live Session 5: creating dashboards in Preset
Wed 1/227:00 PM—8:30 PM (UTC)
Cleaning and transforming data using DBT and SQL
Visualizing data with a Business Intelligence tool
Post-course
Post-course material
Bonus
Improve your SQL skills (optional)
Free webinar on December 6th, 2024
Free webinar on Dec 6th, 6pm-7pm ET.
We will discuss how to break into Analytics Engineering with Daniel Gonzalez - Analytics Engineer at Sweetwater.
For more info and to register for the Webinar: https://www.touchdowncoaching.com/events
or enter your email
Join an upcoming cohort
Analytics Engineering for Data Professionals
Cohort 1
$750
Dates
Payment Deadline
Meet your instructors
Fabrizio
Fabrizio built and scaled both leadership and technical data teams at Uber Eats and Better Mortgage.
As an academic, he published 20+ peer-reviewed articles in top Statistics, Machine Learning, and Medicine journals.
He also teaches graduate courses at Columbia University (in the past: Carnegie Mellon University and Duke University), where he develops the next generations of data leaders.
Mattia
Mattia worked as a technical leader at Amazon Alexa and PayPal, where he contributed to the design and implementation of both experimental and production-grade Machine Learning and Artificial Intelligence systems.
Mattia is also a Teaching Professor at Carnegie Mellon University. Prior to Carnegie Mellon University, he was a Consulting Professor at Duke University. Every year, Mattia helps hundreds of students learn how to solve real-world problems using Data Science and Machine Learning.
Course schedule
4-6 hours per week
Week 1 - Mon, Tues, Thu
2:00pm - 3:30pm EST
- Monday: introduction to the Modern Data Stack
- Tuesday: Snowflake and Fivetran
- Thursday: dbt and Github
Live sessions will be recorded.
Week 2 - Mon, Wed
2:00pm - 3:30pm EST
- Monday: transforming data with DBT and SQL
- Wednesday: dashboarding in Preset
Live sessions will be recorded.
Course project
2 hours per week
Follow the course by implementing your own Data Stack!
Join an upcoming cohort
Analytics Engineering for Data Professionals
Cohort 1
$750
Dates
Payment Deadline
Learning is better with cohorts
Active learning, not passive watching
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
Frequently Asked Questions
Join an upcoming cohort
Analytics Engineering for Data Professionals
Cohort 1
$750
Dates
Payment Deadline