NUS
 
ISS
 
NUS ISS

Data Management for Analytics

Master the skills to manage, govern, and prepare data you can trust — so your analytics and AI deliver results that matter.

Overview

Reference No TGS-2023039680
Part of Graduate Certificate in Analytics for Business Decisions, Graduate Certificate in Analytics Project Management
Duration 3 days
Course Time 9:00am - 5:30pm
Enquiry Please contact ask-iss@nus.edu.sg for more details.

If your dashboards are questioned, your AI outputs are unreliable, or your teams spend too much time cleaning data, the issue is often not the analytics tool, it is how the data is managed. Data Management for Analytics is a practical 3-day course designed for analytics, BI, and data professionals who want to build the skills to manage, structure, and prepare data for reporting, analytics, and AI.

Many analytics projects fail not because of poor visualisation or modelling, but because the underlying data is incomplete, inconsistent, poorly governed, or not ready for use. This course focuses on fixing that foundation. It gives learners the essential data management skills to design data schemas, build ETL/ELT workflows, apply data quality controls, manage privacy and security requirements, and use Generative AI to improve everyday data management and governance tasks.

By the end of the course, you won’t just “understand” data management, you will be able to design and implement practical data management workflows, apply data quality and governance principles to real business scenarios, and leverage Generative AI to support everyday tasks from generating synthetic data to streamlining compliance and policy enforcement. More importantly, you will gain the confidence to make sound data decisions that directly improve reporting, analytics, and AI outcomes.

As organisations scale their AI and data capabilities, professionals who can ensure data is trustworthy and well-governed are increasingly critical,  and this course positions you to be one of them.


 

Register

Registration Instructions

Self-sponsored Participants

  • Register for the course by clicking on the "Register Now" button above
  • You may refer to the User Guide for Learner

Company-sponsored Participants

  • You will have to be registered for the course by someone from your company who has an account on the LifeLong Learning Portal (L³AP)
  • The person in-charge may register you for the course by:
    • Generating a corporate registration link for you to register for the course
      • After the link is generated, you must:
        1. Log in to L³AP by clicking on the "Register Now" button
        2. Click on the corporate registration link after logging in
      • If you do not follow the above instructions, you will be registered for the course as self-sponsored
    • Registering you for the course backend
      • You will still be required to log in to L³AP and complete your registration by clicking on the "Register Now" button above
  • You may refer your HR/L&D POC to the User Guide for Company

Upcoming Classes

Class 1 05 Oct 2026 to 08 Oct 2026 (Full Time)

Duration: 3 days

Time:
09:00am to 05:00pm

Class 2 04 Jan 2027 to 07 Jan 2027 (Full Time)

Duration: 3 days

Time:
09:00am to 05:00pm


Key Takeaways

Upon completion of this 3-day course, attendees will be able:

  • Design and construct database and data schema
  • Construct and implement Data Extraction, Transformation and Loading (ETL/ELT)
  • Augment data management with Generative AI
  • Evaluate and implement data quality, security and privacy for data and analytics
  • Augment data governance with Generative AI


Who Should Attend

This course has been designed for analytics professionals and managers seeking to learn data management skillsets, such as data modelling, data extraction and data manipulation.   

  • Business Analyst
  • Business Intelligence Analyst
  • Data Analyst
  • Data Custodian
  • Data Steward
  • Citizen Data Scientist
  • Citizen Data Engineer


What to Bring

No printed copies of course materials are issued.
Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials.

If you are bringing a laptop, please see below for the tech specs:

 

Minimum

Recommended

Operating Systems

• Windows 7, 8, 10 or
• Mac OS

Laptop running the latest
version of either Windows or
Mac OS

System Type

32-bit

64-bit

Memory

8 GB RAM

16+ GB RAM

Hard Drive

256 GB disk size

 

Others

• An internet connection – broadband wired or wireless
• Installation permissions (non-company laptops)
• Keyboard
• Mouse/Trackpad
• Display
• Power adapter (laptop battery might run out)

DirectX 10 graphics card for graphics hardware acceleration

 


Additional Software Requirements:
• Power BI Desktop



What Will Be Covered

Introduction to Data Management for Analytics

  • Construct the strategy and framework for data management
  • Identify and design the key components of the data ecosystem for analytics

Data Modelling and Design

  • Design data schema for analytics
  • Identify and verify data fields for data analytics modelling, reporting and dashboarding

Data Governance, Risk and Compliance

  • Formulate data governance for business use cases
  • Implement data quality, security and privacy for analytics
  • Assess data ownership of various data sources
  • Evaluate data risk and security for analytics 

Data Lineage, Integration and Interoperability 

  • Verify data sources and data fields
  • Design data consolidation and data lineage and usage approaches
  • Construct and implement Data Extraction, Transformation and Loading (ETL)
  • Integrate dataset for data analytics

Augmented Data Management and Data Governance via Generative AI

  • Revolutionise Data Governance with Generative AI
  • Revolutionise Data Management with Generative AI



    Fees & Subsidies

    SkillsFuture Singapore (SSG) Funding 2024
      Full Course Fees Singapore Citizens & PRs aged 21 years and above 
    (70% funding support)    		 Singapore Citizens aged 40 years and above 
    (90% funding support)    		 Enhanced Training Support for SMEs (ETSS) 
    (90% funding support)
    Full course fee  S$2850 S$2850 S$2850 S$2850
    SSG Funding  - S$1995 S$1995 S$1995
    Nett course fee  S$2850 S$855 S$855 S$855
    9% GST on nett course fee S$256.50 S$76.95 S$76.95 S$76.95
    Additional Funding if eligible under various schemes  - - S$570 S$570
    Total nett course fee payable, including GST  S$3106.50 S$931.95 S$361.95 S$361.95

    Note:
    1. SSG Funding is available to qualified individuals, subject to meeting the attendance requirement and passing of assessment.
    2. All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
    3. SME fees are applicable only to participants who are sponsored by small and medium enterprises.
    4. SSG Funding is valid up to 30 Sep 2024.



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    Certificate

    Certificate of Completion
    Participants have to meet a minimum attendance rate of 75% and are required to pass the assessment to be issued a Certificate of Completion.


    Preparing for Your Course

    NUS-ISS Course Registration Terms and Conditions

    Find out more.

    NUS-ISS and Learner’s Commitment and Responsibilities

    Find out more.

    WIFI Access

    WIFI access will be made available to participants.

    Venue

    NUS-ISS
    25 Heng Mui Keng Terrace
    Singapore 119615

    Click HERE for directions to NUS-ISS

    In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

    Course Confirmation

    All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

    General Enquiry

    Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.



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