Learn to analyse data with Excel, SQL, and Tableau in this beginner-friendly, 10-week course. Gain the confidence to apply these high-demand skills across any industry or role.
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GAIN VITAL SKILLS WITH UNIVERSAL RELEVANCE
TAP INTO A VALUABLE PROFESSIONAL NETWORK
LEARN ON A SCHEDULE DESIGNED FOR BUSY PROFESSIONALS
APPLY YOUR KNOWLEDGE IN REAL-WORLD WORKING SCENARIOS
Software Engineer & Data Instructor
Data Analytics Instructor
Data Analytics Instructor
These experts bring in-depth experience from the field to the classroom each day, providing invaluable insights into succeeding on the job.
GA instructors* are committed to providing personalised feedback and support to help you gain confidence with key concepts and tools.
*GA instructors are subject to their availability
The Data Framework
• Explain the value of data.
• Describe the data framework and how it’s used by analysts.
• Write a specific and testable question given a scenario.
Finding the Right Data
• Describe the data sources available for analysis.
• Evaluate data sets and their variables.
• Determine if a data set can be used to solve a business problem.
Cleaning Your Data
• Use the Filter feature to spot check for problematic data.
• Handle missing data based on industry norms.
• Use conditional formatting to identify duplicates and extreme values within a data set.
• Use Find and Replace to fix issues/errors that are easily identifiable.
• Select a data cleaning strategy based on a given scenario.
Organizing Data With Functions
• Use VLOOKUP and HLOOKUP.
• Use INDEX MATCH.
• Distinguish between the three functions.
Introduction to Data Analytics
• Outline goals, expectations, and logistics.
• Identify the skills and mindset of a successful data analyst.
• Discuss the discipline of data analytics, including topics such as data formats and data ethics.
Data Cleaning and Formulas
• Apply data cleaning best practices, including working with NULLs.
• Conduct exploratory analyses.
• Experiment with common Excel formulas.
Referencing and Lookups
• Build relationships between cells in Excel.
• Manipulate data sets using VLOOKUP.
• Look up values in other tables using INDEX and MATCH.
Aggregating Data With PivotTables
• Apply Excel aggregation functions to data sets.
• Use PivotTables to summarize data.
• Identify common problems and solutions for PivotTables
• Modify data structures with regular tables for efficient workbooks.
Communicating With Excel
• Identify the appropriate visualization types for the data set at hand.
• Create analytics visuals such as bar charts, pie charts, line graphs, histograms, and scatterplots.
• Explore data using conditional formatting for categorization and analysis.
Project: Apply what you’ve learned in Excel and present your process, findings, and challenges to the class, giving and receiving peer-to-peer feedback.
Introduction to SQL
• Navigate a relational database.
• Practice writing and executing SQL queries, including SELECT, FROM, WHERE, and DISTINCT SELECT.
• Work with logical and comparison operators in SQL.
Grouping in SQL
• Work with CASE to handle multiple conditions.
• Practice writing aggregate functions: MIN, MAX, SUM, AVG, and COUNT.
• Use advanced SQL commands such as GROUP BY and HAVING to group and filter data.
Combining Data With JOINs and UNIONs
• Combine data from multiple sources using INNER and LEFT JOINs.
• Compile data using UNION and UNION ALL.
• Compare use cases for JOINs and UNIONs.
Advanced JOINs and NULLs
• Practice the concepts and syntax of advanced JOINs such as EXCEPT, FULL, and OUTER.
• Handle NULLs in SQL
• Practice query optimization techniques.
Subqueries in SQL
• Construct subqueries for multi-step operations.
• Identify subquery use cases for various business scenarios.
• Practice common table expressions (CTEs) with SELECT statements.
Functions in SQL
• Apply string, math, and date functions in SQL to prepare and analyze data.
• Practice writing SQL queries with advanced functions to solve business problems.
Project: Apply what you’ve learned in SQL and present your process, findings, and challenges to the class, giving and receiving peer-to-peer feedback.
Introduction to Tableau
• Prepare data for import into Tableau.
• Navigate the Tableau interface to build visualizations.
• Aggregate measures and dimensions.
• Work with Marks Card and discrete versus continuous dates.
Data Manipulation in Tableau
• Connect to the PostgreSQL server.
• Create calculated fields to analyze data.
• Apply filters to single or multiple worksheets.
Dashboards in Tableau
• Apply visual analytics best practices.
• Design interactive dashboards with parameters, advanced filters, and layout containers.
Data Narratives
• Create stories in Tableau to illustrate data-driven decisions.
• Finalize dashboards and stories for the capstone project.
Capstone Project: Wrap up and reflect on your Data Analytics journey, applying what you’ve learned throughout the course to a real-world data set.
19 Nov - 23 Jan
| Tuesday & Thursday | 8pm - 10pm
Part-Time Course
Learn Excel, SQL, and Tableau to transform raw data and drive powerful analyses.
40 hours
Tuesday & Thursday | 8pm - 10pm
from as low as
RM /month
RM 7,500
excluding admin fees and 6% SST
This course is a HRD Corp Signature Programme course. It is 100% claimable from your organisation's HRD Corp levy. Please contact us for claims process.
Data is an integral part of every successful business. Regardless of industry, companies need to learn how to harness data to make critical decisions. In this course, you will gain a robust and marketable skill set that can be applied to almost any industry or profession.
According to IBM, more than 2.7 million data job openings are expected in 2020, and the need for data-driven decision-makers and functional analysts will be most acute. Learning data analytics can help you advance in your current profession or explore a growing field.
Data Analytics is our best entry-level data course for professionals looking to hone analysis skills and evolve their careers. You’ll find a diverse range of students in the classroom including:
Data analysts who want to brush up on core techniques and formalise their skill set.
Digital marketers, sales managers, product managers, UX researchers, and others who deal with large volumes of data on a daily basis.
Managers who need to tell compelling, data-driven stories to business stakeholders to influence decision-making.
Career-starters looking for a practical skill set to boost their resumes.
Regardless of their backgrounds, this programme attracts students that are interested in manipulating large data sets to solve problems.
Our instructors represent the best and brightest senior analysts from top companies like Atlassian, Capital One, and Deloitte. They combine in-depth experience as practitioners with a passion for nurturing the next generation of talent.
We work with a large pool of experienced instructors around the world.
This is a beginner-friendly programme with no prerequisites. If you are new to data analysis, you will have access to three hours of pre-work to help you prepare for the course, and your Admissions producer may recommend that you take a short Excel workshop. If you already work with basic functions in Excel or have dabbled in SQL, our curriculum will enable you to perform more powerful analyses.
Our Admissions team can discuss your background and learning goals to advise if this course is a good fit for you.
Here are just some of the things you can expect as a GA student:
Yes! Upon passing this course, you will receive a data analytics certificate. Thousands of GA alumni use their course certificate to demonstrate skills to employers and their Linkedin network. GA’s Data Analytics course is well-regarded by many top employers, who contribute to our curriculum and use our data courses to train their own teams.
Yes! All of our part-time courses are designed for busy professionals with full-time work commitments.
You’ll be expected to spend time working on homework and projects outside of class each week, but the workload is designed to be manageable with a full-time job.
If you need to miss a session or two, we offer resources to help you catch up. We recommend you discuss any planned absences with your instructor.
For your capstone project, you’ll select a real-world data set for exploration and apply all of the techniques covered throughout the course to solve a problem. You’ll craft a problem statement, prepare technical documentation, and communicate findings through a stakeholder presentation. You’ll graduate with a polished, portfolio-ready project to showcase your analytical and visualisation skills. We encourage you to tackle a problem that’s related to your work or a passion project you’ve been meaning to carve out time for.
While 1-week students will concentrate on their capstone piece, 10-week students will complete two additional, smaller projects that designed to reinforce what you’ve learned in each unit. Note that the vast majority of project development will be completed outside of class.
Data Analytics is our best entry-level course for professionals wanting to develop analysis skills that can be applied in a wide range of business contexts.
Some Data Analytics graduates who have existing programming knowledge may go on to enrol in a Data Science course and learn more complex analysis techniques involving computation.
For those committed to a career change, the full-time Data Science Immersive programme provides the most direct pathway to data science and other advanced analytics roles.
