By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    analyst,women,looking,at,kpi,data,on,computer,screen
    What to Know Before Recruiting an Analyst to Handle Company Data
    6 Min Read
    AI analytics
    AI-Based Analytics Are Changing the Future of Credit Cards
    6 Min Read
    data overload showing data analytics
    How Does Next-Gen SIEM Prevent Data Overload For Security Analysts?
    8 Min Read
    hire a marketing agency with a background in data analytics
    5 Reasons to Hire a Marketing Agency that Knows Data Analytics
    7 Min Read
    predictive analytics for amazon pricing
    Using Predictive Analytics to Get the Best Deals on Amazon
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: The 5 Most Common Data Relationships Shown Through Visualization
Share
Notification Show More
Aa
SmartData CollectiveSmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Visualization > The 5 Most Common Data Relationships Shown Through Visualization
Big DataData Visualization

The 5 Most Common Data Relationships Shown Through Visualization

SandroSaitta
Last updated: 2014/11/02 at 11:25 AM
SandroSaitta
6 Min Read
SHARE

zach-watson-thumbnailToday’s guest post comes from Zach Watson of TechnologyAdvice. Thanks Zach for contributing to to dataminingblog.com

zach-watson-thumbnailToday’s guest post comes from Zach Watson of TechnologyAdvice. Thanks Zach for contributing to to dataminingblog.com

As the amount of data available to organizations and marketing departments grows, visualizations of that data are growing more complex. That’s not to say that data visualizations are becoming unwieldy – quite the opposite. The increasing amount of information being displayed in visual form helps viewers understand the often convoluted relationships between ranges of data.

However, when presented with the choice to visually represent data relationships, it can be difficult to choose which model to apply. Different types of data work better with specific visualization models.

More Read

analyst,women,looking,at,kpi,data,on,computer,screen

What to Know Before Recruiting an Analyst to Handle Company Data

Tackling Bias in AI Translation: A Data Perspective
Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Banks Merge Data Mining and CRM Tools to Boost Profitability
How Residential Proxies Help Improve Data Gathering

Let’s examine five of the most common data relationships that are being transformed into visualizations.

1. Geospatial

Information on maps used to be set in stone once the project was completed. With geospatial visualizations, sometimes referred to as geovisualizations, users can explore huge amounts of data sorted by geographic details. Interactive elements are common to this model of visualization, and provide insight for a range of uses cases, from political campaigns to large sales organizations.

Displaying data in this manner helps distinguish the regional impact of an organization’s efforts, or a certain local policy or law. This visualization model is used primarily by larger companies since it requires a large amount of data to create real value. Geospatial visualizations often focus on particular silos of information, like data from particular cities or regions of a country.

2. Temporal

Displaying data from a range of time is another common model for visualizing information. Like geospatial models, temporal visualizations include a wide array of applications and specific use cases. For example, steamgraphs highlight the ebb and flow of data around a central x axis.

Temporal visualizations allow viewers to zoom out from particular location, and focus on the increase in absolute activity as represented by the data. Temporal visualizations have been around for a while. Gantt charts are perhaps one of the first use cases in the business community.

3. Multidimensional

One of the most powerful capabilities of data visualization software, multidimensional models create representations of data clusters, which can be difficult to comprehend because of their abstract nature. These new visualizations often take the form of bubble charts, which represent data clusters in bubbles of varying size, as well as tree maps, which group data in categorical fashion.

Similar to many of these relationship models, multidimensional comparison has been around for some time as anyone who’s worked with pie charts can confirm. However, pie charts are very limited in their ability to show the relationships of a large number of categories because of their 2D structure. Newer multidimensional visualizations are much more adept at addressing large amounts of data covering a variety of categories.

4. Hierarchical

Hierarchical data visualizations display data as the name implies: through ascending or descending levels of importance, prevalence, or other metric. Common examples include dendrograms, and variations of tree diagrams, which are distinct from tree maps in that they display data in branches rather than in rectangular spaces.

Hierarchical visualizations excel at imposing rank on data sets, and also work well for displaying sub-categories of broader sets of data. Radial tree models and wedge stack graphs are some of the more visually impressive methods of displaying data in hierarchical fashion.

5. Network

Perhaps the most intuitive model for showcasing relationships between data, network visualizations focus on displaying connections between various data sets. Common models are dependency graphs and node-link diagrams.

As the amount of data available to organizations of all types increases, network visualizations will only become more important. The utility of network visualizations comes from their ability to easily connect disparate types of data. Such connections provide a simple method for exploring a number of data sources.

Connecting different data sets has become a science over the past several years, and visualizations represent the result of long hours of labor. Data isn’t simply for the analytics experts anymore; it needs to be seen and understood by a number of users so they can leverage it for insight. Visualizations are quickly becoming the common ground between data experts and laypeople.

Author Bio

Zach Watson is the content manager at TechnologyAdvice. He covers gamification, healthcare IT, business intelligence, and other emerging technology. Connect with him onLinkedIn.

Share/Bookmark

SandroSaitta November 2, 2014
Share This Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

data breaches
How Hospital Security Breaches Devastate Local Communities
Policy and Governance
analyst,women,looking,at,kpi,data,on,computer,screen
What to Know Before Recruiting an Analyst to Handle Company Data
Analytics
data perspective
Tackling Bias in AI Translation: A Data Perspective
Big Data
Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Best Practices Big Data Data Collection Data Management Privacy

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

analyst,women,looking,at,kpi,data,on,computer,screen
Analytics

What to Know Before Recruiting an Analyst to Handle Company Data

6 Min Read
data perspective
Big Data

Tackling Bias in AI Translation: A Data Perspective

9 Min Read
Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Best PracticesBig DataData CollectionData ManagementPrivacy

Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices

7 Min Read
data mining and crm for banking
Big Data

Banks Merge Data Mining and CRM Tools to Boost Profitability

9 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?