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Data Analytics: Elevate

Gain the confidence to work with data more comfortably in your role, with a real-world context and hands-on experience using Excel, SQL, Tableau and more.

Course overview

What you’ll learn in this course

You’ll have 6 months access to all online course materials, enabling you to study at your own pace and fit your development around your busy lifestyle.

Explore the value of data analytics, recognise types of problems answerable with data and cover some useful mindsets for approaching data. You’ll get familiar with the data analytics pipeline and use cases for key data tools.

  • Recognise the value of data analytics
  •  Key terminology and tools relevant to the data space
  •  Awareness of data communication
  •  Apply introductory Excel skills
  •  Understand how Python is used in data analytics
  •  Apply the full data analytics pipeline to a data challenge

Understand the importance of connecting the high-level business objective (the ‘why’) with the objective for your data analysis. You’ll learn how to research the ‘problem domain’, write a problem statement and set success metrics.

  •  Define the problem, the problem domain and context
  •  Establish which insights are obtainable via data
  •  Translate business goals into data analysis goals
  •  Create a data analysis SMART goal
  •  Set expectations with stakeholders regarding data projects
  •  Apply basic Excel skills to a data problem
  •  Introduction to Python libraries
  •  Create a data analysis project statement of work

Learn how to identify data for your analysis goals and the best data sources. You’ll uncover potential issues related to data collection, including data quality and ownership. You’ll also learn how to make queries to retrieve data from databases.

  •  Data licensing, ethics and privacy
  •  Obtain data from internal and external sources
  •  Relational databases
  •  Apply database skills by using Google BigQuery
  •  Write SQL queries
  •  Extract data from real databases
  •  Combine Python and SQL

Explore common data manipulation techniques, such as converting data types, sorting, filtering and managing duplicates. You’ll also learn how to work with various file formats, such as CSV and JSON.

  •  Understand statistical and computer science data types
  •  Identify different data file types such as CSV and JSON
  •  Apply common data manipulation techniques, such as converting data types, sorting, filtering and managing duplicates in Excel
  •  Apply these same data manipulation techniques in Python

Learn how to use charts to explore data, discover new insights or form your own hypotheses. You’ll learn about different types of charts, how to build them, and how to use them to discover patterns and insights.

  •  Introduction to charts and data visualisations 
  •  Identify charts for exploration and charts for communication 
  •  Analyse types of charts and when each type is appropriate to use
  •  Understand the anatomy of a chart and chart elements
  •  Create charts using Excel and Python
  •  Use chart-creating tools such as Datawrapper and Tableau

Learn how to ensure your data is the best version of itself it can be. ‘Dirty’ data can lead to poor or misleading analysis results. By the end of the module, you’ll know how to identify dirty data and the techniques needed to clean it.

  •  Understand what ‘dirty’ data is
  •  Identify dirty data using Excel, with techniques such as filtering and summary statistics
  •  Clean dirty data using Excel and Python

This module emphasises exploratory data analysis (EDA), which is a great approach for identifying patterns in data. You’ll learn how to combine data from multiple tables, use pivot tables to aggregate data, and answer specific questions using a combination of Excel and SQL.

  •  Understand the concept of EDA and the EDA mindset.
  •  Visualise distributions, relationships and categorical variables
  •  Group and aggregate data using pivot tables and binning data
  •  Combine multiple data tables in Excel and SQL
  •  Apply EDA knowledge to the Python environment (optional)

Get introduced to the practice of data modelling. You’ll learn why models exist, how they can add value to data analysis tasks, and how to identify different types of models. You’ll even take your first steps into modelling by building a few models of your own.

  •  Data modelling and regression basics
  •  Analyse trendlines and R-squared values
  •  Create a simple linear regression model in Excel
  •  Create a simple multiple regression and non-linear model in Excel (optional)
  •  Analyse regression fit and errors
  •  Managing the performance/complexity tradeoff
  •  Introduction to machine learning

Learn how to effectively communicate your findings. This brings the data analysis process full circle, as the outputs are tied back to the problem definition and used to effect change.

  •  Introduction to data storytelling and data dashboards
  •  Analyse data storytelling techniques
  •  Create data stories using Tableau and/or Datawrapper
  •  Apply techniques to communicate geographical data
  •  Personal data project

Focus on dashboard design and construction, covering use cases and the guiding principles for different dashboard builds. You’ll also review a number of sample dashboards and understand the suitability of various dashboarding tools.

  •  Analyse what makes an effective dashboard
  •  Explore different dashboard tools
  •  Create a simple dashboard in Excel or Tableau (optional)
  •  Examine best practice presentation skills, including understanding the audience and storytelling
  •  Create a presentation 
  •  Personal data project

Why study Data Analytics at Academy Xi?

Fees & payment options

We offer a range of flexible payment plans so you can achieve your goals today, and pay at your own pace.


Study Now Pay Later

Choose weekly, fortnightly or monthly repayments over a repayment term of up to 36 months, with no deposit and 100% interest-free.

Weekly payments from

$55 /week


From $55 /week


Pay upfront

Pay for your course upfront to receive a 10% discount on the full amount, and be eligible for any additional special offers.

Total cost of course


Total cost of course



Payment Assist

Convenient payment plans that break up your course repayments into smaller chunks, 100% interest-free.

Flexible installments from

$100 /week


From $100 /week

Frequently asked questions on Data Analytics

Frequently asked questions

Data Analytics is the process of sourcing, cleaning and analysing raw data to identify meaningful patterns, trends and insights. Insights extracted from data can be used to find answers to all kinds of questions, and solutions for even the trickiest problems.

Data Analytics helps us understand the effects of what we’ve been doing, what we could be doing, and any probable outcomes that come with a new course of action. At its core, data analytics tells us what to do next. The ultimate aim is to use hard facts to make well-informed decisions that help a project reach its goals.

Many businesses have a wealth of raw data at their fingertips, but translating it into actionable insights is easier said than done. Data Analytics helps a business tap into a vital resource and better understand its products, customers and competitors, as well as its own operational procedures and capabilities. Armed with this knowledge, businesses are able to identify inefficiencies and opportunities. Because data is not an opinion or a theory, it can act as an impartial source of truth when making important decisions.

Data Analysts rely on a wide variety of tools to be more effective and efficient in their day-to-day work. Some of the handiest tools that Data Analysts use include: 

  • Excel
  • Python Programming
  • SQL
  • Power BI
  • Google Colaboratory
  • Google BigQuery
  • Tableau
  • Datawrapper

In this course you’ll experience flexible and self-paced learning, where students cover course content independently and browse material on our engaging learning platform.  You’ll learn through a combination of:

  • Readings
  • Pre-recorded videos
  • 1:1 support sessions
  • Hands-on activities and practical project work
  • Q&A via chat and discussion boards

We offer three online course formats across design, tech and business that deliver a range of practical outcomes:

  • Transform courses teach job-ready skills and help you launch a new career
  • Elevate courses expand your existing skill set and progress your career
  • Foundations courses teach introductory skills and build a knowledge base

Be inspired by our student success stories

Kanako Chapman

Cost Controller

Data Analytics Elevate

Kanako is a recent graduate of our Data Analytics: Elevate course. After 14 years in accounting, Kanako upskilled and moved internally into a new data analysis role that she’s really passionate about. Read on to find out about Kanako’s Academy Xi experience and how she managed to land an exciting new role auditing and analysing data in her company’s cost control department.

Kanako Chapman, Data Analytics Elevate

Jocelyn Fisher

Project Administrator

Data Analytics Transform

With a passion for problem solving and an eye for detail, Jocelyn is a perfect match for a career in Data Analytics. Find out how the Data Analytics: Transform has helped Jocelyn go from complete beginner to industry-ready in just 15 weeks.

Jocelyn Fisher, Data Analytics Transform

Barry Nguyen

Software Engineer

Software Engineering Transform

Startup Founder, Entrepreneur, Advisor — and now Physiotherapist turned Software Engineer — Barry Nguyen proves that curiosity, passion and continuous learning can help you get ahead of the curve.

Barry Nguyen, Software Engineering Transform

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