This document provides an introduction to data visualization. It defines data visualization as the graphical presentation of data to help decision makers understand patterns and insights. The document discusses the history of data visualization and why it is important. It also outlines some common tools used for data visualization like Tableau and Qlik. Finally, it discusses how data visualization is used in different industries and its future, including emerging multidimensional techniques.
The Future Of Data Visualization
with Gert Franke
OVERVIEW
Data visualization has become increasingly popular over the last few years. Many tools nowadays include some kind of data visualization which gives you insight in usage, the best possible way to travel, the best product offering, etc. Data visualization seems to be a powerful solution for summarising information in a world where the amount of information targeted towards us is increasing every day. But is this the holy grail for processing information? What new possibilities does visualising data provide us? What is the best possible way to present and interact with these data visualizations?
In this talk Gert Franke will briefly show where data visualization comes from, how it now influences our daily life, what the potential of data visualization is and what the future of data visualization might look like.
OBJECTIVE
Show the history, potential and future of data visualization.
TARGET AUDIENCE
People that want to understand the possibilities of interactive data visualizations.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
The history of data visualization
The reasons why data visualization became so hot the last few years
The potential of data visualization
The things we have to be aware of when creating (interactive) data visualizations
What might the future look like with the use of data visualization
AMES 2016 - The Human Side of AnalyticsStephen Tracy
Last year the global analytics industry was estimated to be worth $125 billion in hardware, software and services revenue. Consequently the market has been flooded with more tools, platforms and tech than you can shake a calculator at. When it comes to data, the core challenge many businesses face today seems to have less to do with analytics technology and infrastructure and more to do with finding the right people, talent and skills. In this presentation Stephen will share 10 lessons for building a successful analytics program through a ‘people-first’ strategy.
This is a presentation I gave on Data Visualization at a General Assembly event in Singapore, on January 22, 2016. The presso provides a brief history of dataviz as well as examples of common chart and visualization formatting mistakes that you should never make.
Guest Lecture for the Data Visualization Class at Ateneo de Manila University. Basic design for Computer Science students. For educational purposes only, no copyright infringement intended.
The Future Of Data Visualization
with Gert Franke
OVERVIEW
Data visualization has become increasingly popular over the last few years. Many tools nowadays include some kind of data visualization which gives you insight in usage, the best possible way to travel, the best product offering, etc. Data visualization seems to be a powerful solution for summarising information in a world where the amount of information targeted towards us is increasing every day. But is this the holy grail for processing information? What new possibilities does visualising data provide us? What is the best possible way to present and interact with these data visualizations?
In this talk Gert Franke will briefly show where data visualization comes from, how it now influences our daily life, what the potential of data visualization is and what the future of data visualization might look like.
OBJECTIVE
Show the history, potential and future of data visualization.
TARGET AUDIENCE
People that want to understand the possibilities of interactive data visualizations.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
The history of data visualization
The reasons why data visualization became so hot the last few years
The potential of data visualization
The things we have to be aware of when creating (interactive) data visualizations
What might the future look like with the use of data visualization
AMES 2016 - The Human Side of AnalyticsStephen Tracy
Last year the global analytics industry was estimated to be worth $125 billion in hardware, software and services revenue. Consequently the market has been flooded with more tools, platforms and tech than you can shake a calculator at. When it comes to data, the core challenge many businesses face today seems to have less to do with analytics technology and infrastructure and more to do with finding the right people, talent and skills. In this presentation Stephen will share 10 lessons for building a successful analytics program through a ‘people-first’ strategy.
This is a presentation I gave on Data Visualization at a General Assembly event in Singapore, on January 22, 2016. The presso provides a brief history of dataviz as well as examples of common chart and visualization formatting mistakes that you should never make.
Guest Lecture for the Data Visualization Class at Ateneo de Manila University. Basic design for Computer Science students. For educational purposes only, no copyright infringement intended.
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Bigger and Better: Employing a Holistic Strategy for Big Data toward a Strong...IT Network marcus evans
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by Patrick Hadley, Australian Bureau of Statistics at the Australian CIO Summit 2014
North Raleigh Rotarian Katie Turnbull gave a great presentation at our Friday morning extension meeting about data visualization. Katie is a consultant at research and advisory firm, Gartner, Inc.
Ulrich Homann, Chief Architect, Microsoft Services in Redmond bietet einen exklusiven Einblick, wie Microsoft als Unternehmen die Strategie erhöhter Unternehmenseffizienz, Mitarbeiterproduktivität und Innovationskraft umsetzt, sowie eine strategische Betrachtung zur Arbeitswelt der Zukunft.
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This Presentation allow students to understand the importance of data journalism and uses of Illustrations and graphics by the newspaper organisations..
Presentation for geomarketing students at the VU University, Amsterdam. Three lines of thought: Geography & Business, Locationbased marketing, Social media and the hyperlocal.
Data visualization is an interdisciplinary field that deals with the graphic representation of data. It is a particularly efficient way of communicating when the data is numerous as for example a time series.
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Keynote speech given by Prof. Dr. Diego Kuonen, CStat PStat CSci, on May 15, 2018 at the conference "Big Data for European Statistics (BDES)" in Sofia, Bulgaria; see
https://webgate.ec.europa.eu/fpfis/mwikis/essnetbigdata/index.php/BDES_2018
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.
This will explain you what is data visualization,why we need it,what are the technologies in it ,tools available for it and it ends up with how can we get the excellence in visualization
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1. DATA VIZUALIZATION
A BRIEF INTRODUCTION
PRESENTED BY:-
ANUSHKA GUPTA
ARVIND PUNIA
DIVEK BHATIA
PARUL NIMESH
RISHABH SINGH
SHIVAM AGGARWAL
2. WHAT IS DATA VIZUALIZATION ?
• Data visualization is the presentation of data in a pictorial
or graphical format.
• It enables decision makers to see analytics presented
visually, so they can grasp difficult concepts or identify
new patterns.
• With interactive visualization, you can take the concept a
step further by using technology to drill down into charts
and graphs for more detail, interactively changing what
data you see and how it’s processed.
3. History of Data Visualization
• The concept of using pictures to understand data has been around for
centuries, from maps and graphs in the 17th century to the invention
of the pie chart in the early 1800s.
• Several decades later, one of the most cited examples of statistical
graphics occurred when Charles Minard mapped Napoleon’s invasion
of Russia.
• The map depicted the size of the army as well as the path of
Napoleon’s retreat from Moscow – and tied that information to
temperature and time scales for a more in-depth understanding of
the event.
4.
5. Why is data visualization important?
The way the human brain processes information, using charts or graphs to
visualize large amounts of complex data is easier than poring over
spreadsheets or reports.
Data visualization is a quick, easy way to convey concepts in a universal
manner – and you can experiment with different scenarios by making slight
adjustments.
Data visualization can also:
Identify areas that need attention or improvement.
Clarify which factors influence customer behavior.
Help you understand which products to place where.
Predict sales volumes.
6. Data visualization: Making big data approachable
and valuable
• The insight gained from big data – everything from knowing what
factors influence customers to make a purchase to pinpointing
behavior patterns that can lead to fraud or misuse – can help
organizations improve operations and identify new opportunities.
• But getting to that payoff can be a challenge, because big data is
voluminous and tends to evolve, making it challenging to get a
handle on.
7. Regardless of industry or size, all types of businesses are using data
visualization to help make sense of their data.
1.Comprehend information quickly
By using graphical representations of business information,
businesses are able to see large amounts of data in clear, cohesive
ways – and draw conclusions from that information.
And since it’s significantly faster to analyze information in graphical
format (as opposed to analyzing information in spreadsheets),
businesses can address problems or answer questions in a more
timely manner.
How Is It Being Used?
8. 2.Identify relationships and patterns
Even extensive amounts of complicated data start to make sense when presented
graphically; businesses can recognize parameters that are highly correlated. Some of the
correlations will be obvious, but others won’t. Identifying those relationships helps
organizations focus on areas most likely to influence their most important goals.
3.Pinpoint emerging trends
Using data visualization to discover trends – both in the business and in the market – can give
businesses an edge over the competition, and ultimately affect the bottom line. It’s easy to spot
outliers that affect product quality or customer churn, and address issues before they become
bigger problems.
4.Communicate the story to others
Once a business has uncovered new insights from visual analytics, the next step is to communicate
those insights to others. Using charts, graphs or other visually impactful representations of data is
important in this step because it’s engaging and gets the message across quickly.
Conti…
9. Laying the groundwork for data visualization
Before implementing new technology, there are some steps you need to take. Not only
do you need to have a solid grasp on your data, you also need to understand your
goals, needs and audience.
Preparing your organization for data visualization technology requires that you first:
•Understand the data you’re trying to visualize, including its size and cardinality (the
uniqueness of data values in a column).
•Determine what you’re trying to visualize and what kind of information you want to
communicate.
•Know your audience and understand how it processes visual information.
•Use a visual that conveys the information in the best and simplest form for your
audience.
10. Tools for data visualization
• Tableau Software
• Tableau Software is perhaps the best known
platform for data visualization across a wide
array of users
• This company, founded in 2003, offers a
family of interactive data visualization
products focused on business intelligence.
The software is offered in desktop, server,
and cloud versions.There's also a free public
version used by bloggers, journalists,
quantified-self hobbyists, sports fans,
political junkies, and others.
12. SAS Visual Analytics
SAS is one of the traditional vendors in the advanced analytics space, with a long history of offering analytical insights
to businesses. SAS Visual Analytics is among its many offerings.
The company offers a series of sample reports showing how visual analytics can be applied to questions and problems
in a range of industries. Examples include healthcare claims, casino performance, digital advertising, environmental
reporting, and the economics of Ebola outbreaks.
13.
14. Use of data visualization in industry
Stock market
18. Future of data vizualization
Data visualization is entering a new era. Emerging sources of intelligence, theoretical developments and
advances in multidimensional imaging are reshaping the potential value that analytics and insights can
provide, with visualization playing a key role.
The vast majority of data visualizations today are two-dimensional. However, that’s changing with creative
use of color and size, combination of space and time, and advanced computer graphics.
For instance, neuroscientists Emmanuelle Tognoli and Scott Kelso developed a five-dimensional model
known as the 5-D colorimetric technique, that provides a dynamic and comprehensive view of brain activity
through spatiotemporal display and color coding. Another example is Microsoft’s Holograph, an interactive
3-D platform that can render static and dynamic images above or below a plane for more natural exploration
and manipulation of complex data.
20. As the world becomes increasingly interconnected and interdependent,
opportunities to generate value through data visualization will only
increase.
The Internet of Things will have a profound effect on the role that data
visualization can play in organizations and society, improving our ability
to understand how humans and machines interact with each other and the
environment.
Application of evolving cognitive frameworks, such as Network and
Complexity Theories, will help us better reflect dynamic and intricate
structural dependencies. And advances in multidimensional visualization
will allow us to more effectively synthesize and explore spatiotemporal
conditions.
CONCLUSION
