Data visualization

TalentServe

By Jagadeep Kumar K

What is? data visualization?

Data visualization is the process of using visual elements like charts, graphs, or maps to represent data. It translates complex, high-volume, or numerical data into a visual representation that is easier to process. Data visualization tools improve and automate the visual communication process for accuracy and detail.

Data visualization helps to tell stories by curating data into a form easier to understand, highlighting the trends and outliers.

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Five data visualization techniques?

1.??? charts (bar, line, pie, etc.),

2.??? plots (scatter, bubble, box, etc.),

3.??? maps (heatmaps, dot distribution maps, cartograms, etc.),

4.??? diagrams and matrices.

4 pillars of data visualization?

The foundation of data visualization is built upon four pillars:

1.??? distribution,

2.??? relationship,

3.??? comparison, and

4.??? composition.

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Advantages of data visualization?

·???????? Simplifies complex data.

·???????? Reveals patterns and trends.

·???????? Aids in decision making.

·???????? Improves retention and engagement.

·???????? Increases accessibility.

·???????? Real-time monitoring.

·???????? Identify areas that need attention or improvement.

·???????? Predictive analysis.

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Types of data visualization tools?

1.??? Google Charts,

2.??? Tableau,

3.??? Grafana,

4.??? Chartist,

5.??? FusionCharts,

6.??? Datawrapper,

7.??? Infogram, and

8.??? ChartBlocks etc.

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Conclusion

In conclusion, importance of data visualization is evident in data science, enabling businesses to draw valuable insights and make informed decisions. Both data visualization in data science are vital for a business