SkillsFuture Singapore (SSG)

1. Data Analytics Overview
a. Explain the roles in data analytics and types of analytics.
b. Demonstrate understanding on the steps taken by Data Scientists/Analysts during an analytics project.
c. Understand the sensitivity in the data collection process to ensure clarity and consistency for downstream analysis.

2. Data Preparation
a. Understand the various data types and how they impact reporting.
b. Explain the importance of data quality to data analytics project.
c. Get data from different data sources with different connectivity types.
d. Apply best practices to  profile, clean, transform and load data.

3. Data Modelling
a. Collate the data from different sources by building relationships between them.
b. Aggregate data and  format time-based data for drill down analysis.

4. Visualization
a. Recognise and critic charts and dashboards that are presented poorly (e.g. misleading information, poor use of colours, choice of charts).
b. 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
a. Understand key elements for effective story telling with data
b. Apply the best practices for dashboard design
c. Explain discoveries and insights with the help of visualisations (e.g. charts, tables, dashboards) to support conclusions and recommendations

The course is designed to provide participants with techniques, knowledge and practice on descriptive and diagnostic analytics from data preparation to data modelling and data visualization to support intelligent business decision making with Microsoft Power BI Software.

• General IT technical knowledge
• General IT business knowledge