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?

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

- 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

- 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

- 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

- 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

- 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.