You will uncover the power of data visualization as a tool to explore and explain data and start visualizing data about your company's CO2 emissions. You will be able to analyze patterns and communicate insights precisely and clearly using tools like bar charts, pie charts, and histograms.

Data visualization: who and what?

The goals of data visualization

Let's plot in KNIME

A first dip in the data

Commute modes

Who pollutes the most?

Data Visualization

In this chapter, you will learn a few widely used plots and charts and the basic principles of data visualization: simplicity, clarity, and the wise use of color. You’ll also explore how to represent data distributions, proportions, and relationships with tools like histograms while applying best practices like proper labeling and accurate scaling.

Basic visualizations

Match the chart

Prepare the data for the visualization

Explore relations

Parallel lines

All emissions

One Plot for Each Task

In this chapter, you will focus on more advanced data, particularly time series, and learn how to effectively plot it. You’ll also explore advanced visualizations like geospatial charts while learning preprocessing strategies to handle complex datasets. These techniques will help you uncover detailed patterns and present your data compelling and insightfully.

Advanced visualizations

Recall the use case

Time series and composite visualizations

Emissions over time

Let's draw a line (plot)

Plot together

Advanced Plots and Preprocessing

In the final chapter, you wrap it up literally: you will use components to group visualizations into a composite view, generate an interactive dashboard, and create a PDF report to showcase your findings. Following best practices, you will ensure your visualizations are tailored to your audience and effectively guide their attention.

Dashboards and reports

Spot the difference

Dashboards in KNIME

Interactive dashboard

Text and layout

Report

Congratulations

Dashboards and Reports

Exercises and Datasets

DataCamp vs. Local Experience

One key skill of every data analyst is the ability to create informative and effective visualizations—in other words, to make the data talk.<br><br>
In this course, you will learn the basics of data visualization, including common charts and plots, their use cases, best practices, and key principles like simplicity and clarity. You’ll progress from creating basic visualizations to advanced plots for complex data, including time series and geospatial charts. By the end, you will design an interactive dashboard and generate a report showcasing a company’s CO2 emissions, combining insights from multiple visualizations into a clear and compelling presentation.

<h2>Introduction to Data Visualization</h2> <p>Learn the basic elements of data visualization using KNIME. Create a variety of widely used plots and charts, emphasizing simplicity, clarity, and the wise use of color. You will understand how to effectively represent data distributions, proportions, and relationships, ensuring each visualization is clear and accurately scaled.</p><br> <h2>Advanced Techniques and Applications</h2> <p>As the course progresses, delve into more complex data types with a focus on time series analysis and geospatial visualizations. You will explore advanced techniques for preprocessing and handling intricate datasets, which will prepare you to uncover detailed patterns and offer compelling data narratives.</p><br> <h2>Creating Professional Reports and Dashboards</h2> <p>In the final stages of the course, learn how to synthesize your visualizations into comprehensive dashboards and professional reports. You'll be guided through the process of building interactive components and generating PDF reports tailored to your audience's needs. By the end of this course, you will have the skills to design visualizations that effectively guide and inform your viewers.</p><br>

Data Manipulation in KNIME

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Data Visualization in KNIME

Fondamenti di KNIME

Who pollutes the most?

Data Visualization in KNIME

Esercizio pratico interattivo