Skip to main content

Business Analytics with SQL and Python

Enrol now

Acquire foundational skills in SQL and Python and deliver powerful analysis and predictions for your team or business. 

Enrol now
Select a start date
5 Oct 2020

Time commitment
6 weeks (8-10 hours per week) 100% online
A$ 1200 incl GST


Level up your skills and qualifications as a digital native

Why study Business Analytics with SQL and Python

Business analytics is the process in which data is obtained, cleaned, and presented by teams and organisations to drive useful predictions and insights. Two ways in which businesses do this is through SQL and Python. SQL, or Structured Query Language, is a query that extracts data from tables within a database. Python, on the other hand, is a programming language that has data analysis libraries built on top of it, allowing for data to be analysed and manipulated in order to tell compelling stories and drive business decisions.  

With the opportunity to work on your own data set, or with a data set provided, now’s the perfect time to roll up your sleeves and get hands on with SQL and Python. Develop the critical data wrangling, exploring, analysing, and communication of data skills that will make you highly desirable in the industry.  

What you'll learn
  • The data analytics process  

  • How to determine the right questions and right methods to address a business issue 

  • The wrangling, exploring, analysing, and communication of data 

  • Hypothesis testing and A/B testing for business 

  • An intro to SQL: How to obtain SQL databases, including basic and intermediate queries, joins, and aggregations 

  • An intro to Python: How to rest and manipulate data 

  • Utilise data libraries such as Pandas and NumPy 

  • Forecasting segmentation and classification 

How it works

As part of this course, you will complete one final project; a slide deck presentation where you’ll build and apply a simple data analytics model to a business problem and demonstrate the following learning outcomes: 

  • Utilise SQL and Python to drive powerful analysis and predictions for your team or business 

  • Assess and implement data modelling, forecasting, and classification using introductory SQL and Python functions 

  • Build and apply a simple data analytics model to solve a defined business problem 


This course can be taken as standalone but has been designed to be taken as part of a two-course Business Analytics bundle. For a more comprehensive understanding of business analytics, we recommend that you also complete Business Analytics and Visualisation.  

Find out more in our FAQ section.

The freedom of online study


Get RMIT credentialed

After completing an RMIT Future Skills course, you will earn an RMIT credential which can be validated, recognised and shared on social media platforms.

Course Structure

Module 1

Understanding the data analytics process

Understand how to frame a business question and explore the data project lifecycle 

Define key performance metrics and the data needed to solve a business problem 

Examine a dataset in Excel set to see alignment with a business question

Module 2


Explore various types of SQL and create and insert data into a table 

Run basic and intermediate queries and classify data within a dataset 

Use Join to combine queries for data aggregation 

Develop an Entity Relationship (ER) model 

Module 3

Cleaning and wrangling data

Identify data to clean and artefacts to drill into data analysis 

Connect Python to an SQL database and replicate how to extract SQL data to Python 

Import CSV data into Python and address key business questions 

Module 4

Panda and NumPy

Introduce Panda and NumPy libraries for data analysis and where to use them 

Utilise Panda in your dataset and address missing data analytic functions with NumPy 

Visualise data using Pandas and be introduced to advanced libraries 

Module 5

Interpreting Results

Outline a forecasting model and build a forecast model using Python 

Use segmentation outcomes to test the forecasting model using recency, frequency and monetary value 

Apply static, animated, and interactive visualisation in Python to your dataset 

Use Matplotlib to develop charts that can be used to present insights 

Module 6

Final project

In this module, you’ll prepare for your final project in which you’ll: 

  • Set a business question 

  • Analyse and shape the data to create a data visualisation 

  • Create and present your findings in a slide deck presentation to your audience 

Learn with Industry Experts

Get ready to meet some of the biggest names in the business

Lachlan Russell Expert industry mentor

Our industry mentors are available to provide 1:1 feedback and guidance on your course work. Our mentors on this course include people like Lachlan Russell. Lachlan is an analytics professional at UberEats Marketplace. His work includes producing insightful enterprise-level solutions in industry to field service management, operational supply and demand, customer analytics and machine learning classification problems. Lachlan is a mathematics graduate and past consultant at KPMG working across the finance, telecommunications, utilities, defence and intelligence industries. 

Ansari Imamudheen Subject matter expert

RMIT Online has built our courses in partnership with industry, providing you with the latest industry insights and best practices from the real world of work. Our subject matter experts on this course include people like Ansari Imamudheen. Ansari is the Data and Product Analytics Manager at BetEasy. With over 7 years’ experience in interpreting and analysing data for driving business solutions, Ansari also has graduate and post graduate qualifications in Business Analytics and Engineering and is certified in Tableau and trained in Agile Scrum.

Learner success teamRMIT Online

Our learner success team are here to help you with 1:1 coaching, tips on how to successfully study online, and any questions or concerns you may have. 

Download a brochure

Register your interest to get a free course guide for Business Analytics with SQL and Python.

First name

Last name


Phone number

When would you like to start studying? (Optional)

Are you an Australian citizen or permanent resident?


By clicking Submit, you agree to be contacted via email and SMS about our courses. Local numbers may also be contacted by phone. For information on how RMIT collects, stores and uses your personal information, see our RMIT Privacy Statement.