Big Data Visualization Techniques: An Overview

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Big Data Visualization Techniques An Overview
An image can often convey whats exactly going on
and as per big data visualization is considered,
you may recall statements like a picture is
worth a thousand words. With its data
visualization techniques, though big data did the
vice versa turning facts and information into
pictures, making the decision-making process
easier for the viewers as in recognizing what the
data has to say and what effects are likely to
occur. Before we go to the depths, it would be
perfectly good to consider several basics. What
is Big Data Visualization?
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via sina Big Data Visualization considers the
presentation of almost any type of data in
graphical format, making it easier to interpret
and understand. However, these presentations are
beyond any typical corporate histograms, graphs,
pie charts and any other representations like
this. These include even more complex
representations like fever charts and heat maps,
enabling a better exploration of information,
identification of correlations and unexpected
patterns. Scale is one of the defining features
of big data visualization. Enterprises can store
and manage large amounts of data that would have
taken numerous years for humans to create and
collect. Big Data visualization helps in
ingesting large amounts of raw corporate data
and processes it further into graphical
presentations which make larger analysis
possible within a few seconds. ALSO READ BIG
DATA SECURITY SECURITY ISSUES AND CHALLENGES IN
THE QUEUE Big Data Visualization Techniques There
are different ways of course for presenting data
from various categories. Depending on the cases
and situations, the following techniques may be
used Two-Dimensional (2D) Area
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• Such graphical representations are generally used
  for geospatial presentations i.e to showcase a
  certain geographic area or a specific location on
  the globe. These types of data visualization
  techniques are helpful when analysis on a
  large-scale is required. It is the best option
  to help the representation of voting results,
  demographics, business growth rates, tourism etc.
  The probable techniques of representation under
  this can be
• Area or Distance Cartograms These are usually
  the copies of specific parts of several maps
  which also portray certain additional parameters
  like population size, demography, travel times
  or any other considered variables.
• Choropleth this is a map using different colors
  for various specific representations of varying
  levels of the identified variable. For example
  the biggest inventory stocks or sakes level per
  state.

• via pinterest
• Dot Distribution Map This data visualization
  method uses dots for highlighting the level of
  the examined variable within an area.
• Multidimensional Data Visualizations

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• via tapclicks
• These are known to be the most widespread big
  data visualization approaches. In order to
  create an image that is easy to grasp it
  considers combining two or more dimensions. In
  case of depicting different values from a single
  data set, this is one of the best techniques.
  The probable ways of presentation under this are
  as follows
• Pie Chart This is, of course, one of the most
  popular tools for data representation. A pie
  chart illustrates numerical values, split into
  sectors with angles and with angles and arcs
  proportionally set as per the values
  represented.
• Histogram Representing both, time periods and
  value parameters, a
• histogram is known o be a series of rectangles.
  It makes easier to grasp the dynamics of
  parameter adjustments.
• Scatter Plot This data visualization model is
  known to depict two sets of
• unconnected dots as parameter values.
• Hierarchical Data Visualizations

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• via microsoft
• Sometimes you are needed to show a comparison
  between two or more data value sets.
  Hierarchical or relation data visualizations
  stand out to be perfect for this.
• Some considerable forms of presentations under
  this are
• Dendrogram It is known to be the hierarchical
  clustering of various data sets which makes it
  easier to depict and understand the relations
  between them instantly.
• Sunburst Chart Also known as the ring chart,
  this is basically a pie chart
• with concentric circles which describe the
  hierarchy of various data values.
• Tree Diagram This big data visualization method,
  presents the data structure with tree-like
  relations. These relations are generally
  presented upside down or from the left to the
  right.
• Network Data Models

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• via interaction-design
• When data sets are required to compared and
  related to each other, the network data
  visualization technique arrives as the best way
  of doing so. Here are the considerable
  presentations under this technique
• Alluvial Diagram This is known to be the
  representation of a flow diagram that generally
  depicts the change in data structure over a
  considered period of time or under specific
  situations.
• Node-Link Diagram This is a circular image
  consisting of dots which
• represent dots which further depict lines and
  data nodes and the links between said nodes.
  Using this, the relation between data sources can
  be interpreted and the probable results can be
  recognized.
• Matrix This is a chart or a diagram used to
  represent two or more data sets connected to
  each other via some relations. A matrix helps in
  showcasing the position of data sets against
  each other and also the relation they behold.
• Temporal Visualizations

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• via niemanlab
• Though they look like simple linear graphs,
  temporal visualizations are much more complex
  and descriptive images with several starting and
  finish points and some overlap items measured
  over them creating a descriptive image of
  variable adjustment. Below mentioned are the
  types of data visualization under this
• Connected Scatter Plot It consists of a plot of
  values for two variables that are known to be
  fetched from a data set. Scattered over the
  picture these values are known to be connected
  with a line.
• Polar Area Diagram This might create an image
  like a standard pie chart.
• However, the difference is that the size of the
  sector is depicted by the distance from the
  center with respect to the angle and arc length.
• Time Series This is one of the most used
  examples in case of continuous
• data evaluations over a considered period of
  time. This is one of the best
• data visualization techniques for the
  presentation of historical data.
• ALSO READ IMPORTANCE OF WIREFRAMES, MOCKUPS AND
  PROTOTYPES...
• The above-mentioned data visualization techniques
  would be just the tip of the iceberg. There are
  still many more that can be successfully
  implemented. Approach is not an issue big data
  can make use of both traditional and special
  visualization techniques in order to make it
  understandable for various business users.