What is Data Visualization and Why is it Important?

Data visualization presents information clearly and simply through the use of charts, graphs, and maps. It converts complex data into simple visual representations.

With vast amounts of data in every industry, visualization may assist identify patterns and trends rapidly, resulting in faster and more informed decisions.

In today's increasingly data-driven world, having easy ways to examine and comprehend data is more vital than ever. After all, the demand for data capabilities among employees grows consistently year after year. Employees and business owners at all levels require a grasp of data and its implications.

This is where data visualization comes in useful. With the goal of making data more accessible and understandable, numerous companies use visualizations of data in the form for visualizations to analyze and share data. 

Online data visualization tools

With so many data visualisation tools available, selecting one that meets your requirements should be simple. Before committing to a tool, think about if you require an open-source site or if you can just make a graph in Excel or Google Charts. The standard data visualisation tools listed below may be suitable for your needs. 

• Tableau

• Google Charts

• Dundas BI

• Power BI

• JupyteR

• Infogram

• ChartBlocks

• D3.js

• FusionCharts

• Grafana

Key Elements of Data Visualization

• Data representation involves using graphs, charts, and infographics to display information. Interactivity allows users to explore and change data for deeper insights.

• Real-time updates: Updating dashboards and visual reports with the most recent data

• Customization involves tailoring images to varied audiences and analytical needs.

• A data story delivers information in a structured, narrative-driven style.

Best practices for effective data visualization.

To guarantee that our visuals are powerful and easy to grasp, we use the following best practices:

• Audience-Centric Design: alter visuals to our audience's knowledge. A technical audience might want complex graphs, but a general public benefits from simplified graphics.

• Design Clarity and Consistency: Select the right graph for our data and keep the design clean with inline colors, fonts, and labels. Avoid clutter to ensure clarity.

• Provide Context: Always provide labels, titles, and data source acknowledgments. This helps viewers understand the value of the data and fosters trust in the outcomes.

• Design simulations to be interactive with options like as hints and filters, while ensuring accessibility for all users regardless of device.

Types of Data Visualisation

Visualizing data can be as easy as a bar graph or scatter plot, but it becomes very useful when comparing the median age of UK members of parliament to the median age of the UK population. The list above provides some standard types of data visualisations:

• Table:  A table is a collection of information displayed as columns and rows that may be readily created in Word or Excel.

• Chart or graph: This type of information is presented in tabular form, with data displayed along an x and y axis, typically with bars, points, or lines to represent data in comparison.

• Gantt chart: An Gantt chart is a bar chart which depicts an itinerary and tasks for project management.

• Pie chart: A pie chart divides data into percentages represented by "slices" of a pie, all adding up to 100%.

• Geospatial visualization: This type of visualisation presents data in map form, using shapes and colors to show the link between specific areas, similar to a choropleth or heat map.

• Dashboards: display data and visualisations for business reasons, assisting analysts in comprehending and expressing data.

Importance of Data Visualization.

Data visualization is critical for comprehending and communicating information efficiently. Here are some major reasons why it is important:

Simplifies Complex Data: It reduces complex data by converting it into visual formats such as charts and graphs, which make the information easier to interpret.

Reveals Patterns and Trends: It exhibits patterns and trends that are difficult to discern in raw data or tables.

Saves time: Visuals enable faster data interpretation, allowing users to identify key information at a glance rather than manually scanning through numbering.

Improves Communication: It improves communication by making it easier to explain data insights to others, particularly those who are unfamiliar with the technical details.

Tells a Clear Story: Data graphics walk the audience through the facts step by step, making it easy to draw conclusions and make sound choices.

Conclusion

Data visualisation is an effective technique for portraying information and data in an understandable manner for both yourself and others. It enables users to obtain insights from data and make informed decisions. There are so many visualization tools accessible to designers that it might be difficult to choose which one to employ. Most data visualization tools offer free trials (if not the entire tool), so it's worth trying out a few before settling on one.