Data Analytics with Power BI

About This Course

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