Academy for Continuing Education (ACE)

Organisations across industries are increasingly relying on data for critical decision making. Based on data, companies are able to gain useful insights to guide their strategic direction. For instance, data can help companies decide on which new products to develop, identify investment opportunities, recognise new markets to enter, and better engage with their target customers.

However, many organisations are overwhelmed with data, given the large amount created daily. This is why data analytics skills are in demand as companies try to make sense of the massive amount of data available. Through data analytics, management will also be able to make decisions quicker and more efficiently. Data can be used to identify inefficiencies in operations and help organisations to streamline their operations too.

This course is designed to equip participants with techniques, knowledge, and practise on descriptive and diagnostic analytics. Participants will learn about data preparation, data modelling, and data visualisation to support intelligent business decision making, using Microsoft Power BI Software.

Learning Objectives 

By the end of the course, participants will be able to:

1. Data Analytics Overview
   • explain the roles in data analytics and types of analytics
   • demonstrate understanding on the steps taken by data scientists/analysts in analytics projects
   • understand the sensitivities in data collection process to ensure clarity and consistency for downstream analysis


2. Data Preparation
   • understand the various data types and how they impact reporting
   • explain the importance of data quality for data analytics project
   • get data from various sources with different connectivity types
   • apply best practices to profile, clean, transform, and load data


3. Data Modelling
   • collate data from different sources by building relationships amongst them
   • aggregate and format time-based data for drill down analysis


4. Visualisation
   • recognise and critic charts and dashboards that are presented poorly (e.g. misleading information, poor use of colours, choice of charts)
   • use and interpret common visualisation charts (e.g. Bar, Line, AreaChart, GeoMap, Histogram, PivotChart, Boxplot, Scatterplot, etc.) in the most appropriate way to answer problem statements


5. Story Telling
• understand key elements for effective story telling with data
• apply best practices for dashboard design
• explain discoveries and insights with the help of visualisations (e.g. charts, tables, dashboards) to support conclusions and recommendations

Who should attend?

Individuals who are looking to enhance their careers by applying data analytics at work. Those who are interested to start a new career as data analysts. Business analysts interested to harness Power BI for visualisation.

Entry Requirement 

Participants are expected to have some exposure to Microsoft Office software.

Certification

Participants will be awarded a certificate of completion upon meeting the 75% course attendance requirement.

For courses with assessment component, participants will be awarded the certification of completion upon passing the assessment. Otherwise, a certification of attendance will be issued instead upon meeting the 75% course attendance requirement.