Dates: 2 May, 3 May, 5 May 2023 | 9 am-5.30pm | Classroom Learning
Duration: 3 Days
What is Analytics and why are companies, enterprises and organisations making data speak?
As data keeps increasing, it becomes a high-value asset from which you can extract decisive information. The question is no longer “do we need analytics?” Instead, the focus is on using tools and capabilities to turn this source of raw data into insights and eventually into action.
Data has become the new corporate asset class. In the MIT Sloan Management Review 2017 survey, 55% of companies said they were effective at using data to guide future strategies. Unlike before when analytics was considered the domain of just data experts, the skill is now essential for executive roles in any domain or industry. As data becomes essential to the growth of every business, the need for senior executives who know how to visualize analytics and take data-driven decisions is increasing.
This course covers descriptive analytics which is the upstream process of the insights value chain. It focuses on what has already happened in a business and is the foundational starting point used to inform or prepare data for further analysis down the line. Learn how to reveal the winning combination with human hypothesis-driven input and patterns discovered from tools.
This module is part of Professional Certificate in Business Analytics.
Course will enable participants to:
- Understand sources of data generation
- Learn the tools and techniques to perform data preparation
- Understand how to make use of tools to perform data exploratory analysis
- Generate statistical indicators for reports
- Identify data limitations and understand how to resolve them
- Acquire analytic skills to describe the data
This course will introduce the foundational concepts behind descriptive analytics and the fundamentals of data. It covers data preparation, quantitative analysis, and data visualisations.
Participants will get dirty in the data and dive into the transformation using data exploration tools such as Pivot Tables and Power BI progressively. At the end of the course, you will be able to connect multiple datasets, extract and transform data into a usable format and eventually create a data visualisation report for communication to wide business audiences.
- Exploratory Data Analysis
- Descriptive Statistical Measures
- Data Querying and Visualizations
- Project Work
- Data Preparation
- Practice Labs
Who Should Attend
Any working professional who is interested to have a hands-on experience in descriptive analytics, and/or keen to use analytics tools such as Power BI and Excel in data preparation, data visualization and exploratory data analysis.
As it is an introductory course, learners do not have to be an IT expert or programmer to attend it.
Participants should have a windows system that supports Microsoft Power BI Desktop and Microsoft Excel for the practice labs.
At least a polytechnic diploma.
(Click their photos to view their short biographies)
Ms Samantha Sow
Ms Samantha Sow
Ms. Samantha Sow is currently a Senior Lecturer in the department of Information Systems and Analytics at the National University of Singapore (NUS). She has over 8+ years of experience in Business Analytics and Data Science and she conducts training for both government agencies and corporate clients. Before joining NUS, she lectures at Temasek Polytechnic, teaching Business Analytics and Data Science to professionals, managers and executives (PMEs). Prior to being an academia, Samantha worked in the research and development at Infineon Technologies. Her research and project areas include Business Analytics, Data Mining, Predictive and Prescriptive Analytics.
She has a passion for engaging and inspiring participants to enhance their workplace analytics capabilities and increase business intelligence quotient within their organisations. Her interests lie in the applications of data analytics, predictive modelling and optimization techniques to derive actionable insights for commercial effectiveness. She is familiar with typical analytics tools such as Python, R, and SAS, SPSS and Tableau. She also has working knowledge in the area of Analytics, Data Science and Machine Learning.
Samantha completed her Master of Education from University of Sheffield and graduated from the National University of Singapore with a Bachelor’s in Engineering, First Class Honours. She has also completed THEC (Teaching in Higher Education) and ACTA (Advanced Certificate in Training and Assessment). She is a member of the adult associate educator (AEN) by Institute for Adult Learning (IAL), Singapore.
Her certifications include:
Microsoft Certified Azure Data Scientist Associate. Microsoft Certified Data Analyst Associate. SAS Certified Predictive Modeller in SAS Enterprise Miner. Tableau Certified Desktop Specialist.
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email firstname.lastname@example.org
To register, click Register
TGS-2019507052 (Classroom Learning)
For members of public and NUS Alumnus (without R&G Voucher), please follow the steps below:
Select Short Course / Modular Course -> Apply for Myself -> Browse Academic Modules / Short Courses-> Module/Course Category -> Short Courses -> Browse Courses-> Advanced Computing for Exe (Faculty/Department / Unit)
Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.
Course Fee Breakdown
Singapore Citizens39 years old or younger
Singapore Citizen40 years old or older