Turning Complex Data Into More Accessible Information

A database can contain thousands or even millions of values. Yet a long series of numbers does not always make it easy to understand what is happening. Data visualization represents information graphically, making it easier to explore and interpret.

Tableau is designed specifically for this type of work. It can be used to create charts, interactive visualizations, and dashboards from a variety of data sources.

In CDI College's Artificial Intelligence Specialist – LEA.E3 program, one course is dedicated to Tableau and techniques for presenting data visually.

Why Represent Data Visually?

Consider a dataset containing monthly results for several products across different regions. Looking at individual values can provide precise information, but it can be much more difficult to grasp the bigger picture quickly.

A visual representation can help reveal an increase or decrease, a significant difference, a concentration, or a relationship between variables.

Visualization, therefore, becomes an important part of analysis. It can be used to explore data, better understand what it reveals, and then communicate the results.

👉 Learn more: Data Analysis in Artificial Intelligence: Understanding, Structuring, and Interpreting Information

Choosing the Right Visualization for the Data

Different types of charts answer different questions.

A bar chart can make it easier to compare categories, while a line chart may be better suited to showing changes over time. Other types of visualizations can be used to examine distributions, proportions, relationships, or geographic data.

The Tableau course in the Artificial Intelligence Specialist – LEA.E3 program covers various chart types and the principles for creating visualizations suited to the data being analyzed.

The goal is not simply to produce an attractive chart. The visualization needs to make the information easier to understand without distorting its meaning.

Exploring Data Interactively

A static visualization generally presents a single perspective. Interactive tools go further by allowing users to explore the data themselves.

With Tableau, filters and other features can be used to examine different aspects of a dataset. The curriculum includes interactive features for creating visualizations and dashboards.

The same data source can therefore be explored according to different criteria rather than being limited to a single representation.

Bringing Multiple Visualizations Together in a Dashboard

A chart generally answers a specific question. A dashboard can bring several visualizations together to present different aspects of the same situation.

For example, a dashboard could simultaneously show changes over time, a breakdown by category, and comparisons between several regions.

The challenge, however, is to select the information that is actually useful and organize it coherently. Adding more charts does not necessarily make a dashboard more informative.

The Tableau course covers creating interactive dashboards and organizing visualizations to communicate information effectively.

👉 Learn more: Artificial Intelligence in Business: How Data Supports Strategic Decision-Making

Using Visualization to Explore Data

Visualization is not only useful for presenting the results of a completed analysis. It can also contribute to the analysis itself.

Representing data in different ways can sometimes reveal trends, clusters, unusual values, or relationships that deserve closer examination.

These observations can then guide further analysis and lead to new questions. Visualization becomes a way to explore data rather than simply a final presentation step.

👉 Learn more: Hands-On Artificial Intelligence Projects: Learning by Doing

Communicating Results Clearly

An analysis can be technically rigorous without necessarily being easy to understand for someone who was not involved in the work.

The choice of charts, titles, highlighted information, and overall dashboard organization can influence how the results are interpreted.

Data visualization, therefore, requires both technical skills and the ability to communicate information clearly so that different people within an organization can use it to understand a situation or support a decision.

Tableau and Power BI: Why Learn Both?

Tableau and Power BI can both be used to create data visualizations and interactive dashboards. Learning both within the same program allows students to explore different approaches to data visualization.

In the Artificial Intelligence Specialist – LEA.E3 program, Tableau and Power BI are covered in separate courses.

Both are part of a broader education that also includes databases, statistics, R, Python, machine learning, and deep learning.

The objective, therefore, goes beyond learning how to use a particular software tool. It is about developing the ability to work with data and communicate the information it contains.

An Important Skill When Working With Data

Knowing how to analyze data is essential, but the results also need to be understood and presented effectively.

In the Artificial Intelligence Specialist – LEA.E3 program, Tableau helps students develop skills in visualization and dashboard creation that complement their learning in data analysis and artificial intelligence.

The ability to turn raw data into a clear visual representation can make information more accessible and useful in an organizational setting.

FAQ

1. What is Tableau used for?
Tableau is a data visualization tool that can transform data into graphical representations and create interactive dashboards. It can be used both to explore data and to present analysis results in a more accessible way.

2. What is the difference between Tableau and Power BI?
Tableau and Power BI can both be used to visualize data and create interactive dashboards. In the Artificial Intelligence Specialist – LEA.E3 program, they are covered in separate courses, allowing students to become familiar with different data visualization methods and environments.

3. Why is data visualization important in artificial intelligence?
Artificial intelligence projects often involve large amounts of data. Visualizations can help explore that data, identify trends or unusual patterns, and communicate results to people who were not necessarily involved in the analysis.

Explore Further

👉 Artificial Intelligence: Understanding the Field and Career Opportunities

👉 Programming in Artificial Intelligence: Python, R, and Databases at the Heart of the Training

👉 Expert Systems and Artificial Intelligence: Tools for Decision-Making

👉 Learn More About CDI College's Artificial Intelligence Specialist – LEA.E3 Program