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features
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What is ZingChart?

Value Boxes are an essential feature for smaller datasets, providing clear visibility of each node's exact values. When enabled, these boxes prominently showcase the value associated with each node, making it easy for users to comprehend the data. However, in situations involving slightly larger datasets, displaying value boxes for every single node may create visual confusion, prompting the use of tooltips that allow users to view a node's value on demand. For instances where tooltips fall short in delivering sufficient information, crosshairs present a simple yet effective way to analyze a spectrum of values. In the case of very large datasets, where users need to zoom in significantly to identify node values, the ability to magnify specific points helps reduce the difficulty of focusing on the data. Furthermore, the inclusion of scroll bars significantly improves the navigation experience, enabling users to move through the dataset more efficiently. The preview window plays a dual role by assisting users in monitoring their current zoom level while also facilitating quick adjustments to the scroll position. Collectively, these features empower users to engage with the data efficiently, regardless of the size of the dataset, ensuring that they have the tools necessary to derive meaningful insights. This comprehensive approach to data interaction enhances user experience across various dataset scales.

What is Tom Sawyer Perspectives?

Tom Sawyer Perspectives is an extensive platform that enables the development of sophisticated graph and data visualization applications specifically designed for enterprise requirements. This integrated graph visualization software development kit (SDK) boasts a user-friendly graphics-based design and preview interface. By effectively linking to multiple enterprise data sources, the platform utilizes robust graph visualization, layout, and analytical technologies to address the complexities associated with big data. With Tom Sawyer Perspectives, developers can streamline the creation of high-quality, data-focused visualization applications that are ready for implementation. The application development process is supported by two primary graphical modules: the Designer and Previewer, which aid in visualizing and analyzing the distinctive data needs of each project. In the Designer module, developers are empowered to extract or create schemas, data sources, bindings, rules, views, filters, and search capabilities. Additionally, the Designer provides options for customizing toolbars, tooltips, context menus, and specific graphical behaviors for better data viewing and editing, which significantly boosts user engagement. Collectively, these features equip developers with all the essential tools needed to construct advanced applications that cater to a wide range of analytical demands, ultimately fostering innovation within enterprise environments.

Media

Media

Integrations Supported

AWS Marketplace
Amazon Neptune
MongoDB
MySQL
OrientDB
SAP HANA

Integrations Supported

AWS Marketplace
Amazon Neptune
MongoDB
MySQL
OrientDB
SAP HANA

API Availability

Has API

API Availability

Has API

Pricing Information

$249 one-time payment
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

ZingChart

Company Website

www.zingchart.com

Company Facts

Organization Name

Tom Sawyer Software

Date Founded

1992

Company Location

United States

Company Website

www.tomsawyer.com/perspectives/

Categories and Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

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