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    Event Profile
    Class/
    Online
    Classroom
    Date May 09, 2025
    Time 9:00am to 5:00pm
    Venue Holiday Inn Singapore
    Orchard City Centre
    11 Cavenagh Road
    Singapore 229616
    Fee
    9% GST will apply
    SGD 550.00
    3 & above: SGD530.00 each
    For Member
    SGD 522.5
    3 & above: SGD503.5 each
    NoteTwo tea breaks and set lunch or buffet will be served. Limited complimentary car parking coupons are available upon request.

    Participants are required to bring their laptops with MS Excel (ver 2010 or later)
    Other Date(s)1) Dec 02, 2024
    2) Feb 24, 2025
    3) Aug 01, 2025
    4) Nov 05, 2025
    Trainer
    Activity
    You may reach us via
    T: 6204 6214
    E: info@ccisg.com
    Alternatively, you may send below details to register
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    Participant(s)
    Name, Job Title, Email
    "Data is the new oil"
    - The Economist, May 2017

    In this data age, the ability to extract value from data is a highly sought after by both individuals and organizations. While data analytics is often associated with hard skills such as database management, programming and statistics; hard skills alone are not enough. It requires the right mix of soft skills to contextualize the problem, make sense of the analysis and communicate it in a concise, coherent and compelling fashion to drive action.

    This is one of a series of three one-day online workshops. Each workshop is modular in nature, addressing different aspects along the analytics value chain.
    • Data Analysis - a 1-day workshop that focuses on the technical aspects of mining data for objective insights
    • Data Visualization - a 1-day workshop that focuses on presenting data in accessible forms to get the right message across using data visualizations
    • Data Storytelling - a 1-day workshop that focuses on presenting analyses and proposals in a concise, coherent, and compelling fashion to facilitate decision-making

    About this workshop

    This workshop aims to provide a broad but practical overview of the entire analytics value chain, with a specific focus on data management and analysis. Attendees will get the opportunity to get their hands "dirty" with large data sets and experience what it takes to deliver objective insights. This is targeted at professionals and managers in non-analyst roles but may be required to work with or make sense of data and analyses in their work.
    Objective
    By the end of this course, the participants would be able to:
    • Understand what data analytics is and what it takes to deliver value
    • Develop analysis frameworks through problem definition, hypotheses development and identification of data requirements
    • Gain practical data analysis skills through descriptive and inferential analysis exercises with MS Excel
    • Gain exposure to various analytical and visualization techniques and tools to glean insights from the data
    Outline
    1. Analytics in Action
    • Case studies - See how some notable organizations have successfully deployed analytics to great effect

    2. What is analytics?
    • Defining what analytics is...and isn't; how and what it takes to create value
    • An introduction to the Analytics Value Chain
    • An overview of Big Data, Artificial Intelligence and Machine Learning in the context of Analytics and today's data driven world

    3. Translating Data into Insights
    • Building an Analysis Framework
    • 6-step framework from problem to data, insights and decision
    • Seeing the 6-step framework in Action - Oakland Athletics
    • Group exercise: Building an Analysis Framework
    • Analytics Techniques to Connect-the-Dots
    • Exposure to Data Management concepts; such as system vs calculated fields, blank vs zero values, joining/blending data tables, data types and managing databases

    4. Statistical Analysis Concepts for Business Users
    • Introduction to descriptive statistics - Variation in All Data, central tendency and variability
    • Going beyond descriptive to inferential analysis - including Central Limit Theorem, trends analysis, regression analysis, survival analysis etc.
    • Class Exercise: MS Excel Analysis (pivot table, descriptive, correlation, multiple regression)
    • Fallacies and Limitations of analytics - False positives, Correlation vs Causation etc.
    Who should attend
    This workshop is designed for managers, professionals and staff at all levels who want to learn and improve their understanding and skills in data analytics, particularly in applying analytics to problem solving. The course is suitable for participants across all industries and job functions. Participants are required to have basic MS Excel skills; no prior knowledge of data analytics required.
    Methodology
    Trainer takes a practical approach to analytics, and therefore the workshop emphasizes practical analytic skills through learning of key principles and analytics skills. A combination of lectures and hands on exercises are designed to enable participants to acquire those practical skills. This workshop utilises MS Excel for the computer-based exercises.
    Testimonial
    "Fantastic clarity and very succinct. The trainer's wealth of experience and expertise have been very valuable."

    "Hands on experience on applying what we have learnt almost immediately so that we understand the merits and difficulties in doing"

    "Lots of real-life examples. The trainer is relatable, fluent, and definitely knows his stuff very well. Highly recommended trainer"
    Derrick Yuen's Profile
    MBA, BEng, Founder and Principal Consultant

    For more than a decade, Derrick has led engagements to help clients liberate their data for value creation; be it through workshops, consulting or data solutions. His engagements span multiple functions, sectors and geographies; including Pharmaceutical, Engineering, FMCG, F&B, Government, HR , & Finance across Asia Pacific

    In a prior life, Derrick led the formation of the Global People Analytics Centre of Excellence (COE) for a MNC with >US$30 Billion revenue and helped several FYT clients established their own data analytics functions.
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