Dates: 5 Feb, 6 Feb, 7 Feb 2024 | 9am-5.30pm | Classroom Learning
Duration: 3 Days
Course Overview
The business analysis plan represents a blueprint of the work a business analyst has to perform in business needs analysis.
Strategy Analysis describes the work of a business analyst to identify, understand and expand on the business needs, considering the capabilities of the organisation to address those needs, and elaborate ways to achieve goals and objectives in such ways as is best aligned with the relevant strategies. This course teaches the various areas strategy analysis encompasses, including Current state analysis, Definition of the future state, and Define change strategy.
This course is part of Professional Certificate in Digital Business Analysis.
Course Objectives
Upon completing the course, the learning is able to:
- Understand what Business Analysis is
- Understand the role of a Business Analyst in the entire Systems Development Life Cycle
- Develope skillsets a Business Analyst must have to perform effective business analysis
- Understand the five components in the knowledge area of Business Analysis Planning and Monitoring
- Learn how to carry out Business Analysis Planning and Monitoring
- Learn how to perform Strategy Analysis
Who Should Attend
Business Analyst, Product Management / Development
Prerequisites
Diploma (or equivalent) with 3 years working experience, preferably in the IT industry.
Course Convener
(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.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
GST shall apply at prevailing rates.
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Code: TGS-2022011517 (Classroom Learning)
TGS-2022011607 (Synchronous e-learning)
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older
