SQL Master Class For Data Analysis
What you'll learn
- Install and use SQL Server database engine and studio
- Analyse data looking for patterns and behaviours
- Expertly code quantitative analysis using SQL
- Write SQL using LAG(), NTILE(), OVER, PARTITION logic and many more analytics functions
- Understand Primary and Foreign keys
- Understand the difference between DML and DDL
- Understand the relational database model
- Make data driven decisions in your enterprise
- Master all types of table joins (incl. Complex Apply joins)
- Answer those gnarly interview questions, yes we will always have those !
Requirements
- Only have a Mac ? You can use Virtual Box, Windows Server Trial edition and SQL 2014 Express or later
- Want to learn from a rated Top-responding instructor (Yes, I answer Q&A within 24 hours or less!) ?
- As you will learn the A-Z here, start easy then boom - the hard work of data analysis starts
- This course is presented using SQLServer 2014 Express which is free from Microsoft (& later versions e.g 2016 Express can be used)
Description
Greetings,
With so much data stored in SQL databases, how can we get at it ?
You use SQL to get at this data, no matter what the SQL Database product is (e.g SQL Server, Oracle and many more).
Coding SQL to analyse data can be a daunting and complex task, hence the reason for building this course.
In this course I will teach you how code SQL to perform data analysis in order to answer complex questions that you will encounter daily in your job.
Ask yourself these simple questions ...
Do you know all of the TABLE JOIN types that can be applied in a SQL query ?
Have you ever used OUTER APPLY, which is so easy and powerful to use ?
Can you write a running total in a single line of SQL ?
Where do you use a ROLLUP statement and why would you use it ?
What is LAG() ?
If you could not answer these simple questions then this course will definitely change all of that for you.
You definitely should know all of this to survive the SQL environment you work in !
All course materials are provided e.g. Sample databases (with real data), code scripts, practice exercises and quizzes.
Don't forget, there is a 30 Day money back guarantee if this course does not deliver what you expected.
Best Regards
Paul
Data Analyst and Visualisation Engineer
Who this course is for:
- Data Analysts and Data Scientists
- Students
- DBA's
- New graduates
- Technical marketing people
- Those looking to acquire new skills
- Research shows students don’t learn by hearing or seeing, they learn by doing, a model often called active learning.
Featured review
Instructor
- 4.6 Instructor Rating
- 17,393 Reviews
- 136,964 Students
- 7 Courses
Who Am I ?
I am a Data Analyst that is passionate about data (even at home e.g. Energy Billing Analysis) based in Queensland, Australia.
My early career background is in programming (which I still do today in my spare time for fun!)
I moved across to data analysis 20 years ago with SQL Server Reporting Services , Analysis Services. For ETL I worked with DTS later to become SSIS which I loved working with.
In 2012 I started working with QlikView and progressed to Qlik Sense as soon as it was beta released. Of course that was in parallel with QlikView projects both in Commercial and Government installations.
2015 saw my foray into part time teaching here on Udemy with Qlik and SQL courses and have taught over 129K students how to do analytics and have an average rating of 4.6 which is not too bad.
COVID hit us hard but I was grateful to have my teaching work and income to tide my family & I over as businesses and corporate offices shutdown.
Since 2023, I have been doing more on the AI side, experimenting with ChatGPT workflow integration for analytics & app development, as a result I compiled my first AI themed course and published here on Udemy - ChatGPT & Qlik Sense: Application Development Master Class this is where prompt engineering meets Qlik Sense for the full development cycle. ChatGPT has many surprises in this area, many are good , some are frustrating, yet it all gets back to how we interact with a Large Language Model i.e. effective prompting.
As for 2024, I will continue the AI journey with a foray into PowerBI more on that later into the year.