Factors to Consider Before Designing Big Data Visualization

Big data visualization is the
simplest, convenient and interactive technique to illustrate the connection
within data. Traditionally, businesses used graphs, bars and charts to present
relationship in data. However, when it comes to large volume of data or big
data, traditional techniques do not fulfil the requirements and mostly fail to
show this relationship.

Big data visualization imparts
an artistic visual representation of given information, leveraging more
interactive and animated illustrations to establish connections among massive
data with better user understanding. Now let us understand what UX designers
have to consider before the implementation of big data visualization. 

Factors to be Considered
before Implementation of Big Data Visualization

Comprehend the Problem

Before providing any solution
to a problem, it is necessary to gain in-depth knowledge about the problem in
the first place. This will allow you to come up with the most accurate

Big data visualization allows
users to understand big data in the simplest way possible and analyze it to
make better decisions. And to achieve this, the UX designers must understand
the problem that needs to be resolved using visualization. The designers must
try to dig out what the user wants to see and examine from visualization. 

Defining the problem will help
the UX designers to create the most appropriate big data visualization, helping
users to achieve their goals. 

Know Your Users

Once you get an insight of the
problem, its time to find out about the users who are likely to use the
designed visualization. Knowing your users will help you to understand their
level of proficiency and comprehension of advanced visualizations. The UX
designers carry out a thorough research to identify the users. 

These users and their
behavioral patterns are observed and analyzed by the designers, which will
allow them to understand the goals they want to achieve from the solution. User
involvement is an important aspect to start with big data designing. 

Overall, a deeper
understanding of different users, their behaviors and goals will guide the UX
designers to develop a better solution that will improve user experience.

Select Appropriate
Visualization Type

The visualization fulfils its
purpose only when the users can easily understand the pattern and trends in the
big data. Since each visualization has its own purpose and usage guidelines, it
is of utmost importance to select the right visualization type depending upon
the available data and user understanding. A UX designer must have a piece of
adequate knowledge about the changing trends in visualization approaches. 

Factors to be considered by UX
designers before the selection of Visualization type:

  • Come up with an appropriate
    design and layout of the visualization for the convenience of users. 
  • Chose the visualization type
    based on available data. If the visualization type does not align with the
    data, it will of no use to the targeted users.
  • User capability in
    comprehending the data and their level of expertise in understanding
    visualization approaches.

Scatter plots, Polar area
diagrams, Time series sequences, Tree diagrams, Ring charts, Sunburst diagrams,
Density map and Cartogram are some standard big data visualization types. 

Include Relevant

What happens when a lot of information,
irrespective of its importance, is provided to us? It gets a bit tricky for us
to understand the data. The same happens when irrelevant data is included in
the visualization. It will clutter the view and make it difficult for the users
to comprehend the relationship within the data. Here, the UX designer’s
responsibility is to identify data that are less important or least likely to
impact decision making, and eliminate them.

Meanwhile, the most valuable
data must be highlighted and given a prominent space on the visualization. This
will make it convenient for the users to interact and analyze the data, and
make better decisions.

Visualization technique serves
the purpose to convert big data into visual representation, making it easier
for the users to comprehend it in the simplest way possible. Being interactive
in nature, big data visualization enables the users to filter and navigate the
data for better understanding. Prior to implementing the visualization, UX
designers must understand the users and their problems, and come up with the
best visualization type matching the available data. Considering these
practices will improve the big data visualization experience of the users.


  • 6 March, 2021
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