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You can have data analysts and other data researchers gather all the best, most useful information, but if the clients and users can’t understand it, it’s useless. So, the data must be presented in easy-to-use formats that the average person can understand.
That’s why we are using data visualization. As the old saying goes, “a picture is worth a thousand words.
What is Data Visualization?
Data visualization is the process of communicating and translating data and information in a visual context, usually employing a graph, chart, bar, or other visual aid. Visualization also uses images to communicate the relationships between various sets of data.
Importance Of Data Visualization.
Here are some reasons why data visualization is important for presentations:
Easy interpretation: Visuals such as charts, graphs, and maps are designed to make data easy to interpret. They present information in a visual way that can be easily understood and remembered by the audience.
Clarity: Visualization can help to clarify complex information by presenting it in a simple and concise way. This is particularly useful when dealing with data that might be difficult to explain or understand without visuals.
Engaging: Visuals are more engaging than text and can help to maintain the audience's attention throughout the presentation. This is particularly important when dealing with long and complex presentations.
Memory retention: People are known to be highly visual creatures. Studies have shown that people are more likely to remember information presented visually. Data visualization can help to ensure that the key points of a presentation are remembered long after the presentation has ended.
Persuasion: Data visualization can be used to persuade the audience of the presenter's argument or point of view. By presenting data in a clear and concise way, the presenter can make a compelling case for their argument.
In summary, data visualization is an essential tool for presentations as it can help to clarify complex information, engage the audience, improve memory retention, and persuade the audience of the presenter's argument.
The advantages of data visualization include:
Gives the reader the means to quickly absorb information, improve insights and make faster decisions.
Provides an easy means of distributing information that offers users more opportunities to share their insights with everyone involved in the project.
Imparts an increased understanding of what steps an organization must take to improve itself.
Offers the ability to attract and maintain the audience's interest by giving them the information they can understand.
Gives the decision-makers the means to quickly act on findings, deliver successful outcomes faster, and have fewer errors.
Eliminates the need to excessively rely on data scientists because it is more accessible and easily understood.
What are the different types of visualizations that can be made using Tableau?
Tableau offers a wide range of visualizations, including:
Bar charts
Line chart
Scatter plots
Heat maps
Geographic maps
Treemaps
Pie charts
Gantt charts, and more.
The Best Data Visualization Examples
FUNNEL CHART
Here is the example of fennel chart using medical dataset.
Funnel chart with provider specialty
Caption:
Count of Provider Specialty. Color shows details about Provider Specialty. Size shows details about Provider Specialty. The marks are labeled by count of Provider Specialty and Provider Specialty. The view is filtered on Provider Specialty, which keeps Cardiology, Pediatrics, PrimaryCare and Surgery.
COLUMN CHART
Caption:
Count of Provider Name for each Provider Date on Staff Year broken down by Provider Specialty. Color shows details about Provider Specialty. The marks are labeled by count of Provider Name. The view is filtered on Provider Specialty, which keeps Cardiology, Pediatrics, PrimaryCare and Surgery.
DONUT CHART
Caption:
AVG(0) and AVG(0). For pane AVG(0): Color shows details about Provider Specialty. Size shows count of Provider Specialty. The marks are labeled by Provider Specialty and count of PatientMRN (AmbulatoryVisits). The view is filtered on Provider Specialty, which keeps Cardiology, Pediatrics, PrimaryCare and Surgery.
BUBBLE CHART
Caption:
Provider Date On Staff Year and count of PatientMRN (AmbulatoryVisits). Color shows details about Provider Date On Staff Year. Size shows count of PatientMRN (AmbulatoryVisits). The marks are labeled by Provider Date On Staff Year and count of PatientMRN (AmbulatoryVisits). The data is filtered on Provider Date on Staff, which ranges from 1/1/1993 12:00:00 AM to 9/11/2013 12:07:56 PM.
Creating a dashboard in tableau
Dashboard definition
A dashboard is a way of displaying various types of visual data in one place. Usually, a dashboard is intended to convey different, but related information in an easy-to-digest form. And oftentimes, this includes things like key performance indicators (KPI)s or other important business metrics that stakeholders need to see and understand at a glance.
Example dashboard
Once you’ve created one or more views on different sheets in Tableau, you can pull them into a dashboard in two simple steps:
Step 1: Open a dashboard sheet: select Dashboard from menu, then New Dashboard
Step 2: Add views to your dashboard by dragging sheets onto the dashboard.
Here you have created a basic dashboard. You can add more tableau features as per the requirement.
I appreciate you taking time to read this blog. Your thoughts matter, so feel free to share your opinions in the comments below. Stay tuned for more insightful content.
THANKS!