If you are data scientist enthusiast and looking for data visualization guide for beginners then you should check out this data visualization guide for beginners that consists of why data visualization is important for beginners, types of data visualizations and benefits of data visualization. Here https://www.intellectyx.com/blog/data-visualization-guide-for-beginners/

1. A Comprehensive Guide to
Data Visualization
Presented by: Intellectyx.com

2. What is Data Visualization?
Data visualization is a technique that converts complex data into simple, crisp
and strikingly interactive images that present the required information instead
of long and boring texts.
These visual objects include infographic, dials and gauges, geographic, maps,
detailed bar, sparklines, heat maps, pie, fever charts etc

3. History of Data Visualization
Data visualization has got ancient roots from maps and graphs in the 17th century to the pie chart in
the early 1800s. The earliest known data table was designed in 2nd century Egypt which recorded
astrological details to assist navigation. In the 17th century, Rene Descartes invented the Cartesian
coordinate system, the X and Y axis graph that offered the first visual representation of quantitative
data. In statistical graphics.

4. Why Data Visualization is Important?
Data visualization is an innovative method of showcasing complex data using graphs or images
rather than using reports or large blocks of texts to depict complex information generally.
This saves time and helps in delivering an effective presentation which in turn saves everyone’s time
to boost productivity. Moreover, it allows experimenting with different situations by making suitable
adjustments.

5. Data visualization software plays an important role in big data and analytics as they can
be helpful in gathering a summary of a large amount of data efficiently. Despite offering
so many benefits, data visualization can also:
● Identify major and minor areas within the organization that requires
improvement.
● Break down the factors that influence customer behavior.
● Help to understand which product should be kept where.
● Figure out sales totals.

6. Types of Data Visualization
Temporal
Hierarchical
Network
Multidimensional
Geospatial

7. Temporal
For a data visualization to be temporal, it should be linear and one-dimensional. In
simpler terms, it represents the lines which can either be unequaled or intersect with
each other.
Temporal data visualization includes the following:
● Scatter Plots
● Polar area diagrams
● Time series sequences and timelines
● Line graphs

8. Hierarchical
Hierarchical data visualizations indicate the ranking and order of various data and objects in a
company or organization. For example, the tree graph with a simple linear path which allows data
flow from left to right or top to bottom.
Other Hierarchical data plots consist of the following forms:
● Ring charts
● Tree-map charts
● Sunburst diagram graphs
● Circle Packing
● Dendrogram chart

9. Network
Network data visualization allows users to demonstrate the link by connecting various data sets.
Under this network, the users communicate through the intricate networks that link one data set to
another.Few of the common types of network data visualization include –
● Alluvial diagram charts
● Node-link diagrams
● Network diagram charts
● Word cloud plots
● Non-ribbon chord diagram plots
● Parallel coordinates plot

10. Multidimensional
Multidimensional data visualization consists of the following varieties
● Steam graphs
● Pie charts
● Scatter Plots
● Histograms
● Timetable charts
● Stacked area graphs

11. Geospatial
Geospatial data visualizations display information about physical areas. For instance, geospatial
maps which depict regional maps with data mark.
● Density plot
● Cartogram
● Dot distribution map
● Choropleth
● Heat map
● Flow map

12. The Future of Data Visualization
Data visualization is marking its entrance in the new era. It is advancing from art to science with the
introduction of next-generation technologies and the evolution of apparent frameworks giving rise
to new opportunities. Majority of data visualizations is two-dimensional. Neuroscientists are
inventing ways to develop a five-dimensional model called a 5-D colorimetric technique.