DSAI

Fundamentals of Data Wrangling, Analysis & Visualisations

Enquiry
Programme Code D120
Domain
General Digital Literacy
Data Science & AI
Level
Foundation
Learning Partner(s)
Republic Polytechnic
Duration
4 Days
Format In-person
Rating
Competencies
Machine Learning Statistical Techniques Scripting Exploration Analysis Data Storytelling Data Collection Charts & Dashboards Data Quality
Job Roles
Public Service Officer (non-ICT&SS)

Overview

Harness the power of data to gain perspectives you never thought available. This programme will provide you with a good foundation to conduct data wrangling, perform data analysis, create effective visualisation charts, build interactive dashboards and compose convincing data-driven stories using Microsoft Excel (Power Query, PivotTables and PivotCharts) and Tableau to support data-driven business decisions.

Key Takeaways

At the end of this programme, you will be able to:
  • apply data cleansing and data transformation techniques using Power Query, a free function within Microsoft Excel
  • apply mathematical and statistical functions to derive insights from the data
  • create PivotTables and PivotCharts to calculate, summarise, analyse, and visualise data
  • apply visualisation principles for creating effective visualisations
  • create and interpret visualisation charts
  • build interactive dashboards for monitoring key metrics
  • create data-driven stories for communicating key insights

Who Should Attend

  • Please refer to the job roles section.
  • Ideal for Public Service Officers who work with data in Microsoft Excel and would like to prepare data for analysis, create visualisation charts, dashboards, and data stories using Microsoft Excel (Power Query, PivotTables and PivotCharts) and Tableau to support data-driven business decisions.

Prerequisites

You should have basic IT literacy.

Programme Structure

This programme will cover the following topics:

Day 1 & Day 2 (Using Microsoft Excel: Power Query, PivotTables and PivotCharts)
  • Data Collection
  • Data Wrangling
  • Data Exploration & Analysis
  • Data Mining Techniques
Day 3 & Day 4 (Using Tableau)
  • Data Visualisation Principles
  • Tableau 101
  • Interactive Data Visualisation
  • Interactive Dashboard
  • Data-Drive Stories

Full Fee

Full programme fee

S$1140

9% GST on nett programme fee

S$102.60

Total nett programme fee payable, including GSTS$1242.60

With effect from 1 Jan 2024

NOTE
Funding is available for this programme. Please visit the Learning Partner’s website to find out about the updated programme fee funding breakdown, eligibility, terms and conditions.

Upcoming Classes

Class 1
20 Feb 2025 to 25 Feb 2025 (Full Time)
Duration: 4 days
When: Feb - 20, 21, 24, 25
Time : 9.00am - 5.00pm
Class 2
06 Mar 2025 to 11 Mar 2025 (Full Time)
Duration: 4 days
When: Mar - 06, 07, 10, 11
Time : 9.00am - 5.00pm

How To Register


Agency-sponsored

Step 1 Apply through your organisation's training request system.

Step 2 Your organisation's training request system (or relevant HR staff) confirms your organisation's approval for you to take the programme. Your organisation will send registration information to the academy.

Organisation HR L&D or or equivalent staff can register directly through the learning partner's registration portal.

Click here to register for 20 to 25 Feb 2025 run.

Click here to register for 6 to 11 Mar 2025 run.


Step 3 The learning partner will inform you whether you have been successful in enrolment.

Testimonials

The programme notes for Excel and Tableau were very helpful, especially the step-by-step guide for the exercises. The content and case studies were useful for learning as well.

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The use cases from the facilitators with years of work experience were very insightful. They were able to foretell what issues we may face and also give historical perspective on how things have evolved as well as the pros and the cons.

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I learnt how to do data cleansing in Excel, data visualisation via pivot tables/charts and using Tableau to visualise data. The lab work to solve business problems was also important as well, as it got us to think about what questions/stories our charts should tell that are important to address the business problems.

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