Analysing and Visualising Data

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Explore different analytical techniques and find out how to present data effectively.

Less than 30 minutes
Shared Digital Guides

Standardising data collection and automating reporting with Power BI

Format: Webpage

Duration: Up to 30 minutes

Audience: Intermediate

Account creation/sign in required: No

Description: Use this guide to create customised data dashboards that help your team understand organisation data without spreadsheets. It avoids manual repetitions of reporting tasks and makes it easier to work with dense or high volumes of data. 

User rating: 4/5 (based on 2 reviews)

More than 10 hours
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Data Visualization with R

Format: eLearning

Duration: 12 hours

Audience: Advanced

Account creation/sign in required: Yes

Description:  In this course, you will learn the Grammar of Graphics, a system for describing and building graphs, and how the ggplot2 data visualization package for R applies this concept to basic bar charts, histograms, pie charts, scatter plots, line plots, and box plots. You will also learn how to further customize your charts and plots using themes and other techniques. You will then learn how to use another data visualization package for R called Leaflet to create map plots, a unique way to plot data based on geolocation data. Finally, you will be introduced to creating interactive dashboards using the R Shiny package. 

User rating: This resource hasn’t been reviewed yet. Evaluate it here once you have worked through the content.


 

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Data Analysis with R

Format: eLearning

Duration: 16 hours

Audience: Advanced

Account creation/sign in required: Yes

Description:  In this course, you'll learn important techniques for preparing (or wrangling) your data for analysis. You will then learn how to gain a better understanding of your data through exploratory data analysis, helping you to summarize your data and identify relevant relationships between variables that can lead to insights. Once your data is ready to analyze, you will learn how to develop your model and evaluate and tune its performance.

User rating: This resource hasn’t been reviewed yet. Evaluate it here once you have worked through the content.

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