SQL for Data Analysis: Solving real-world problems with data
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SQL for Data Analysis: Solving real-world problems with data
A simple & concise mySQL course (applicable to any SQL), perfect for data analysis, data science, business intelligence.
Requirements
- No coding experience required.
- No data experience required.
- No ‘math brain’ required.
- Requirements: Eagerness to learn, sense of humour, and a career to build!
- The lessons are targeted to ‘everyday people’ with a can-do attitude and a healthy aversion to reading textbooks.
Description
Summary
Forget the dry, old, textbook approach to learning code. Forget endlessly drilling syntax.
This course puts SQL in context and gets you solving real-world business problems from Day 1.
You’ll play the role of a data analyst at Australia’s largest fictional consumer bank, with a uniquely rich relational database at your fingertips. This context brings SQL to life and makes it easier for you to understand deeply and quickly.
With this new approach, you’ll be surprised to see that SQL is fun and simple to learn. My course guarantee is that you’ll go from zero to functional SQL coder within the weekend.
Best features in a nutshell
- In plain English, with business contextand fun analogies to explain the otherwise dry syntax.
- Unique database, using a fictional bank relational database with incredibly rich transaction data to keep the course interesting and relevant.
- Focuses deep on the absolute basics, to get you the strong foundationsrequired for a data career.
- Doesn’t cost money! If you sign up now while it’s free, you have lifetime free access, even as the course grows and becomes paid.
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My story and building the course
My SQL learning experience was not ideal. When I started work I hadn’t the slightest idea what data was, let alone the power it brings to those who wield it skillfully. I took probably a year longer than necessary to master the SQL for data analytics. Even though I was practicing everyday on the job, I was slow to understand new concepts and struggled to remember new syntax.
Now as a full-time data analytics and insights manager, I have the hindsight to know it should have been much easier.
The main ingredients missing for me were:
- Structure
- What is important, what isn’t, and why.
- Context
- Analogies, interesting examples, and plain English explanations. Bringing it to life!
So I’ve taken what was lacking in my learning experience and build a course around it. Specifically, here’s why my course stands out:
- Structured
- We learn what you need for on the job data analysis using SQL, no more less.
- The topics are covered in an order that makes sense and helps you build on past learning.
- You understand why each lesson is important, where it sits in the grand scheme of SQL.
- In context
- SQL shouldn’t have to be dry or boring, so I have used realistic business problems and analogies.
- You’ll be playing the role of a data analyst at the largest fictional company in Australia, the Royal Bank of Australia, solving problems to drive sales, improve marketing reach, and manage customers.
- Knowing why you’re learning the syntax, you’ll learn faster.
- Hands on/practical
- You’ll practice writing SQL in every single lesson.
We are going to have fun too, investigating cryptocurrency trading among customers, and even learning about Australian animals!
Why learn SQL?
Most successful companies today are data-driven.
- They record every bit of information about their business (e.g. customers, sales).
- They store that information (called data) in complex databases.
- And they draw insights from the data to improve their business.
That’s where SQL comes in.
The only way to gather data and transform it into valuable business insights is to combine SQL and a smart analyst like you.
It’s with SQL that companies know answers all sorts of where do my customers prefer to shop? Who was incorrectly charged fees? Why are sales going down?)
And as you may have noticed in the Promo, SQL is a great skill to build your career
Data careers, in data analysis (business analysis), data science, & data visualisation (business intelligence).
- SQL is needed to actually find and handle data in most organisations.
- The data handling and management skills learned via SQL are fundamental to understanding data in general, and are useful even if you don’t use the SQL language (rare).
- Access to data can make you powerful in organisations. It’s hard to argue with an analyst armed with well-prepped data and a solid numbers-based argument.
Marketing, product management, and tech sales:
- SQL (and the accompanying data skills) are a great way to stand out in marketing and product.
- Marketers and product managers propose changes to improve the business.
- Nowadays, any proposed change needs a strong case to support it.
- Data is the foundation of any strong business case.
- Therefore marketers and product managers with data skills can put together stronger cases, get more initiatives approved, and grow their career faster.
Why start with mySQL? mySQL is:
- Very common, used by major companies and organisations across the world, such as Uber, Netflix, Spotify, and JPMorgan.
- Free and easy to set up.
- Similar to other forms of SQL like Microsoft SQL Server, PostGre SQL, Oracle SQL, Teradata SQL.
Note on the Short Version of the Course
I have decided to launch the course in the first instance as a free, shortened version. It is an excellent introduction to the basics of handling data.
Meanwhile, the full paid version is on the way, including lessons on summarizing, joining, and end to end problem solving. Sign up now while it’s free and enjoy all the additional lessons for free when they arrive shortly.
Who this course is for:
- You want to stand out in interviews for your dream job in data analysis, business intelligence, or data science.
- You’re a student wanting a taste of what real-world data analysis is like.
- You’re a product manager, marketing manager, or commercial manager, short on time but need to level-up in data skills to stand out in your career.
- You’re a budding data scientist: SQL is critical for feature engineering, which is a large part of any data science role. Plus, SQL is a much faster and easier route to data than Python.
- You’re already a data analyst using a different language but have moved to a company that uses SQL.
