Today, data may well be the "most valuable currency". Do you agree with this saying ?
The utilisation of technologies leads to an accumulation of data, fuelling the need for skilled individuals who can smartly analyse them to tell facts from fiction, spot upcoming trends and seize opportunities. Data mining encompasses a range of computer technologies aimed to turn your everyday data into meaningful insights for you to improve your business performance.
Discover actionable insights from data to meet business objectives using descriptive, predictive and prescriptive analytics become all the more important in today's day and age. You will get to understand what has happened to your business, discover why it happened and how to harvest and monetise your data to find better solutions to solve daily business problems.
- Introduction to data mining and Artificial Intelligence (AI) concepts
- Learn practical strategies on how to leverage on Descriptive, Predictive and Prescriptive Analytics
- Discover actionable insights from data and customer behaviours
- Leverage on data findings to enhance customer experience and increase profits
- Practical hands-on session to appreciate analytics
- Identify and make use of various latest data analytic tools to carry out data analysis work
- Understand the different methods and usage of data collection
- Spot trends, similarities and differences in sets of data
- Gain better insights in deriving solutions and conclusions to formulate actionable plans
Who Should Attend
Business leaders/owners, Data Analysts, Marketers or anyone who is keen to explore the world of data analysis to assist in understanding their business and daily work
Consulting Director, Integral Solutions (Asia) Pte Ltd & Adjunct Lecturer at National University of Singapore (NUS)
With more than 23 years of practical experience in enabling businesses to benefit from Artificial Intelligence (AI), Machine Learning, Data Mining and big data, Irene has amassed good experience of best business practices in Big Data, Business Analytics and Artificial Intelligence from a wide array of industries (including Banking & Finance, Telecommunications, Wholesale & Retail, F&B, Education and Manufacturing). Armed with a Marketing Degree and a MBA specialising in Entrepreneurial Management, Irene trains business leaders/users on how to leverage on data to derive meaningful insights to achieve higher ROIs on direct marketing programs, discover cross selling opportunities, gain insights in bundling of products, offering the right products to the right target group at the right time through the right distribution channels. She has led and implemented numerous successful big data projects in various businesses and across different industries.
She has led the national survey to explore SMEs and e-business in Singapore. She is also the Singapore researcher for APEC’s ‘Capacity Building for APEC Women’s Entrepreneurs in the Age of the 4th Industrial Revolution’ 2018. Through her participation in research and business projects, she has acquired a wealth of experience in relation to business issues in SMEs. An adjunct lecturer at NUS, Irene specialises in Data Mining and the application of AI for Customer Acquisition & Retention for more than 5 years. She developed and taught Singapore WSQ Certified Course "NICF - Enhanced Customer Acquisition and Rentention : An Information-Centric Approach" which helps Marketers and Analysts in their data work.
Irene is also the Vice President of Strategies & Development at Association of Small & Medium Enterprises (ASME). She is the Chairman of the SME Talent Program and the SMECentre@ASME, the latter set up by Enterprise Singapore (ESG) to provide more holistic and comprehensive business advisory and assistance services to local entrepreneurs and SMEs.
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- No cancellation will be allowed upon registration but attendance by a replacement delegate from your company due to exigency could be facilitated. Please notify SBF of the change with at least 3 working days’ notice prior to event to enable logistical arrangements for the replacement.
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Ref No: SB200024
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