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.
Business Analytics with SQL and Python
Acquire foundational skills in SQL and Python and deliver powerful analysis and predictions for your team or business.
- Time commitment
- 6 weeks (8-10 hours per week), 100% online 100% online
Level up your skills and qualifications as a digital native
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.
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
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.
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.
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
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
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
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
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
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
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.
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.