Is Big Data Visualization ‘Big’ or ‘Small’
9:56 PM Pearl Zhu No comments
Big Data visualization can be big enough to show executives big picture, but
needs to be nimble enough to stay focus.
Data Visualization will change how you think about the world. Right now there is a
significant knowledge gap between having the data, interpreting it, and finally being
about to visualize it. It demands multiple skill sets which are rarely present in most of
the analytics team. So what is focal point for data visualization, and how to make it
Visualization is the best way to really understand Big Data. It was hard enough with
smaller data sets to get a real grasp on the meaning of data without visualization. You
have to be able to interpret and draw a conclusion based on what you are seeing and
that often comes down to being taught how to interpret what you are seeing. You can
only combine these two things if you know what you are looking for. Visualization data
is best way to present information, because it is in people nature to receive visual
information. It is very perspective to develop visualization methods which can leverage
multi-factors in discovering 'big signals'.
The ability to combine art and science is like finding a world-class champs, the
general principle in understanding anything is to perceive with as many senses as
possible. Being able to hear it and seeing it would give a much deeper understanding
and data visualization goes a long way in improving human understanding of big data.
While data visualization is important for understanding, it’s governed by personnel
needs, likes and interpretation. For example some people are able to interpret the data
well when it’s a bar chart, some will like to have a line chart. Intelligence of the system
to highlight deviations and create meaning forl forecast is the need what all business is
'Lightweight’ Visualization to draw meaningful Insight out of it. Although
visualization might not be a new term and for years businesses have been building a
presentation layer of dashboards, widgets, etc... the focus is now on building analytics
and platforms that allow users to discover value in some piece of information that's
available in its raw form and be able to draw meaningful insight out of it, rather than a
design / schema heavy approach where one had to ask a question first to look at how
the information can be visualized. One of the great challenges of broader acceptance of
richer data visualization experiences will be robust filtering or distilling of irrelevant
data or content. In a lot of cases, many data visualization tools immediately loose the
audience because they are trying to over process and visualize "big data" repositories.
It's the old problem of "fire hosing" a customer with too much information.
Visualization can make this worst. Some of the best uses of visualization have been
simple, small and targeted visualizations of customer problems.
There is definitely a balance (of complex data and simple solution) that needs to
be found--it has to be understandable given the complexity of most multidimensional information, yet simple enough that people will actually find meaning
from it--and maybe even more importantly, find the tool usable! IT may talk a lot about
on-time and under-budget, but that becomes meaningless if no one uses the tool-usability has to be a factor that is considered. The key is that visualization is an
important approach to communicating insight. But it has always been thus,
visualization is not a new tool in businesses or life. Data visualization has changed how
we think about the world; it's been doing so for longer than software vendors have
existed. Even industry leaders with their legacy Bread & Butter products find
visualization area enticing. Looking forward for smooth and seamless integration of
these data visualization products to the main stream products and also solve the new
buzzing Big Data puzzle
Visualization is often one of the best ways to convey big and small data,
contextually. The ideal visualization is one that enables decision makers to see a high
level view of the data and then be able to drill down to different sublevels.
Visualization is often one of the best ways to convey big and small data, contextually,
that helps to explain and portray one or more outcomes. It's not the only way to
present Big Data, it's not about a list of products either (although they do help). It's a
function of good design and analysis. Visualization software needs to be able to throw
up data often with the ability to go down to the last minute detail. A number on a
graph often needs to explode right down into the details of every record. That's what
Big Data is asking of Visualization software now.
Visualization is important, but visualization is just the start to exploring Big Data.
Companies need to move beyond visualization to Visual Analytics to truly gain insights
into their Big Data.Big Data visualization can be big enough to show executives big
picture, but needs to be nimble enough to stay focus. Visualization is no doubt the best
way to get the understanding of the data, but it should be used in coordination with
effective Analytics to present the contextual picture of the data
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