Unit 1: Initial Software Engineer Screening
|
|
|
Python is an easy-to-learn programming language that is ideal for those looking to explore careers in data engineering.
We start from the ground up and talk about everything from variable declaration to importing prebuilt modules. If you have worked with other programming languages but want a quick introduction to the basics of Python.
This lecture assumes no prior programming experience.
|
|
|
|
|
In this lecture, we will teach you how to combine your existing knowledge of Python with tools like Pandas and Numpy.
Pandas is an essential tool in data engineering. It’s the database equivalent of a dataset and many operations are performed by first putting data into Pandas.
|
|
|
|
Data Systems In The Enterprise
|
Business Analytics 101. We’re going to talk about the business context in which you’ll be doing your job.
In this lecture, we are going to survey the topic of business analytics from the top down. We’re going to examine how organizations use data. We’ll look at various database management systems. Finally, we’ll take a look at common data storage technologies that you might run into in the real world.
|
|
|
|
Relational Theory Part 1: Transactional Data Models
|
You gotta know what a crumpet is to understand cricket. By the same token, you have to understand transactional databases before you can dive into dimensional modeling.
Dimensional modeling relaxes the assumptions of transactional models. You need to understand the original ruleset so you can understand why those rules are relaxed when we move to dimensional modeling. So, we need to master dribbling before we try to dunk.
This lecture goes into more detail than SNMR002 or MNGT100.
|
|
|
|
Relational Theory Part 2: Dimensional Data Models
|
This is not a data modeling class, but you need to understand how dimensional models are built so that you can better understand how to interact with them. This lecture goes into more detail than SNMR002 or MNGT100.
|
|
|
|
SQL Server At 10,000 Feet
|
Here is where we begin to understand our operational environment. We will take a look at what SQL Server has to offer at a high level.
|
|
|
|
A Grey’s Anatomy of Database Objects
|
This is a vocabulary class. We’re going to talk about all the various kinds of database objects we will be using in the class.
|
|
|
|
SQL Server Management Studio Dollar Ride
|
At this point, you know enough that we are going to kick the tires and light the fires. First, I’m going to give you a cockpit check out on SSMS. Then, I will take you on an e-ticket ride of the various SQL Server subsystems SSMS is used to manage that you will need to know to complete this class successfully.
|
|
Unit 3: Introduction to SQL Fundamentals
|
|
|
In this lecture, we will talk about the various basic techniques used to yank data out of a database. This lecture, more than any other lecture, will be the closest to “learn all this stuff for free on the internet.” Despite that, it is still littered with our “secret sauce” of keeping it practical and real world.
|
|
|
|
Intermediate Level SQL Techniques
|
In this evolution, we will go through the various kinds of joins.
Once we have mastered joins, this opens up a whole new world of possibilities. We continue with our discussion from lecture seven with the added fun of joins.
|
|
|
|
|
This lecture covers all the stuff that you will not find in other SQL classes. We are going to go over the G.I. Joe, Kung-Fu grip, Secret Squirrel aspects of T-SQL that Microsoft and the Deep State don’t want you to know about. Like, did you know that T-SQL has UNDOCUMENTED functions?!
I intend to teach the controversy!
|
|
|
|
SQL Basics For Reports Development
|
Here is where we start learning how to deliver business value with math. We will go over the various methods to crunch numbers and get executives the answers they need to make decisions. This lecture brings together everything you have learned in Unit 2 and is particularly valuable for future reporting analysts.
This lecture teaches you how to send T-SQL downrange to destroy…I mean, provide value to the enterprise with business analytics solutions.
|
|
Unit 4: Advanced Tactical SQL
|
|
|
Understanding how to store the 1s and 0s on disk is an opportunity to speed up processing. Being efficient with your disk space is one of the skills that will set you apart from your peers.
|
|
|
|
SQL Server Programmability
|
In this lecture, we will go over the standard programming elements common to most programming languages and how they are implemented in T-SQL. We’ll also go over views, stored procs, and user-defined functions, but no triggers because reasons.
|
|
|
|
High Performance Data Processing
|
By now, you are in the top 1% of all data engineers. The elite. The BEST of the best. This lecture will make you better. I’m going to teach you how to write your code right to the edge of the envelope, to write queries that execute faster than you’ve ever executed before.
In this lecture, we’re going to go over various aspects of loading a data warehouse individually before joining the concepts together in later lectures to produce full ETL solutions. We’ll also introduce Python to the mix so you can see how Python and SQL play together.
|
|
Unit 5:
SQL Weapons School
|
|
The Data Warehouse ETL Framework Pt 1.
|
In this lecture, we will go over the conceptual aspects of the DW ETL Framework. This lecture is basically an audiobook of the documentation. It is optional, but you will still be responsible for the information in the lecture as it will show up on exams.
|
|
|
|
The Data Warehouse ETL Framework Pt 2.
|
In this lecture, we continue our conceptual discussion from lecture 17. Then we start getting into the nitty-gritty details of some of the sample code that comes with The Framework.
|
|
|
|
|
This lecture is a grab bag that consist of the following topics:
Exchanging Data With Third Parties
Getting Operational With DataOps
Performance Tuning
Developing Data Pipelines with Agile Methodology
Master Data Management
|
|
|
|
Setting Up An Enterprise Grade ETL Environment
|
In this lecture, we will go through the steps of implementing the Data Warehouse ETL Framework. We’ll also finish our discussion of the various sample code offered in the framework.
|
|
|
|
High Speed Data Warehouse Development ETL Edition
|
In this lecture, I’m going to show you how to build an actual data warehouse ETL process using the resources of the Warehouse ETL Framework.
We will go over the usage of the data model creation tool. Then we’ll finish up with a discussion that will prepare you to work on the final lab that also functions as the traditional hairy, stress-inducing final project that is a rite of passage of all college students everywhere.
When you have successfully completed the final project, you will have production-grade code that you can show a potential employer.
|
|
Unit 6: Live Fire Exercises
|
|
Data Engineering Challenges
|
Congrats on getting this far, but all you have now is a license to learn!
Once you pass the final exam, you will be given access to a series of data engineering problems to solve that you can use to keep your skills sharp until you land work.
Following the ethos of “train like you fight”, these problems stem from some issueI had to solve for a client over the past 20 years.
If you can solve these problems, then you’ve got what it takes to do this work.
|
|