The Specialist Diploma in Business Analytics equips students with the knowledge and skills to apply data analytics techniques to derive insights and create predictive models from diverse business data. This will institute data-driven business decisions and achieve competitive advantage.
Upon completion of the programme, graduates will be able to:
- Adopt best practice in data governance, manage of diverse data to support business goals
- Build data engineering pipeline to prepare data for the downstream visualisation and analytics
- Perform data analysis and visualization for data-driven business decisions
- Apply statistical concepts and techniques for data analytics
- Utilise machine learning techniques for predictive analytics to address the business needs
- Apply the concepts, process and techniques of text mining to transform and analyse textual content
- Identify business needs of stakeholders for successful analytics
Target Audience
Diploma or degree level graduates and professionals who want to enhance business analytics knowledge and skills to value-add to current profession.
What is so unique about this programme?
The SDBA program covers the business analytics project’s full life cycle with emphasis on data management, visual predictive modelling and text analytics.
What are the tools/programming languages/platforms used in this programme?
- MySQL
- Snowflake
- Alteryx
- Power Automate
- Microsoft Excel
- Orange
- Tableau
- Python
- R
- KNIME
- SAS Viya
How often do I need to attend the course?
The course is made up of 2 terms (each term spans across 15 weeks) where 3-4 modules will be taken per term. Each module has 10 or 20 lessons, excluding a 2-week mid-term break. Lessons will be conducted via Face-to-Face on RP campus, and home-based-learning (Lectures and Lab)
Course commences in April and October.
| Number of Lessons |
Duration |
Three lessons / week
(2 weekdays+1 weekend OR 3 weekdays)
*1 module at a time |
Weekday: 6:30pm - 9:30pm /
Weekend: 9:00am – 12:00pm
|
What will I get out of this
I started off with zero knowledge in analytics. The Specialist Diploma in Business Analytics had equipped me with relevant knowledge and skills that allow me to pursue my studies further in the field of analytics, as well as getting me a job in the industry that I desired. A very big ‘thank you’ to the lecturers. They’re doing a great job.
Participants will be awarded the Post-Diploma Certificate (PDC) upon successful completion of each certificate programme. The Specialist Diploma in Business Analytics will be issued upon meeting 50% of attendance requirement and passing the assessment criteria of both PDCs.
| Certification (120 hours) |
Modules (30 or 60 hours) |
| Fundamentals of Business Analytics |
- Introduction to Data Management
- Data Wrangling
- Data Visualisation for Business Decisions
- Data Visualisation for Enhanced Business Insights
|
| Advanced Business Analytics |
- Statistics for Data Analytics
- Predictive Analytics with Machine Learning
- Text Analytics
|
This includes self-learning hours in the form of e-learning, assessments, case study analysis and revision required by the module.
Module Synopses
1. Post-Diploma Certificate in Fundamentals of Business Analytics Introduction to Data Management
This module covers the concepts of data management from data governance to data architecture, data modelling and data access. It aims to equip students with knowledge and skills to manage variety of data sources from data in local database to large volume data in big data cloud storage. Students will learn to interpret relational and non-relational data models and manage data in structured database and big data architecture.
Data Wrangling
This module introduces the concepts, tools and techniques of data wrangling. Through building an automated data wrangling pipeline, data from diverse sources are collected, explored, cleansed, enriched and optimized and ready for the downstream visualization and analytics process.
Data Visualisation for Business Decisions
This module aims to equip students with the knowledge and skills to analyze and visualise data for more informed and timely business decision making. Students will be trained to conduct data analysis, interpret results, apply visualization techniques, design data stories, create dashboards to support data-driven business decisions.
Data Visualisation for Enhanced Business Insights
This module aims to equip students with advanced knowledge and skills to address more complex visualization and analytics scenarios. Students will be exposed to a comprehensive set of tools and libraries to create static and interactive visualizations to support data-driven business decision making.
Statistics for Data Analytics
Statistics for Data Analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. The aim of this module is to equip students with knowledge and skills in statistics to handle applications in business analytics. Python or the R software are used to demonstrate the handling of datasets and to perform statistical analysis.
Predictive Analytics with Machine Learning
This module aims to equip students with a comprehensive foundation of data mining processes, machine learning algorithms and hands-on experience to identify data trends and build descriptive and predictive models with an emphasis on business application. Using supervised and unsupervised machine learning techniques, students will learn to resolve business problems using data mining and predictive modelling by going through the entire cycle of business understanding, data understanding and preparation, data modelling, and testing and evaluation of models.
Text Analytics
This module covers the process of data analytics for unstructured textual data from various sources such as databases, websites or social media, from text-preprocess using NLP (natural language processing) to create transformed structured data and apply different text and data analytics techniques based on business requirements, and finally integrate with visualization to draw insights for the business.
Please click on the "Register" button to view the updated course schedule and fees on the Skills Training & Enhancement Portal (STEP).
Applicants should possess at least a local diploma qualification or equivalent in business, engineering, technology, or any other disciplines from recognised institution.
Applicants who do not meet the entry requirements may be considered for admission to the course based on evidence of at least 5 years of relevant working experience or supporting evidence of competency readiness. Suitable applicants who are shortlisted will have to go through an interview and/or entrance test. The Polytechnic reserves the right to shortlist and admit applicants.
Conditional Offer
Graduating student (in final academic year) from a local polytechnic may apply for the programme.
Click here for more information on how to apply for the programme and receive a Conditional Offer.
Please click on the "Register" button to view the updated course schedule and fees on the Skills Training & Enhancement Portal (STEP).