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What is InAppBI?
The fastest way to integrate Analytics into your application involves a straightforward and customizable process that is also cost-effective. With the ability to connect to and model a variety of leading data sources, you can extract essential information and create models that meet your specific business objectives. By querying and visualizing this data, you have the opportunity to merge various models to produce powerful analytics and deliver insights in multiple formats, such as interactive dashboards. In addition, you can implement and scale your analytics solution across any type of infrastructure, whether it be on-premise, cloud-based, or a hybrid environment, all while ensuring high levels of security and performance. This method enables software developers to convert application data into valuable insights and uncover new revenue streams, while allowing business users to generate operational reports and data visualizations independently, without the need for IT intervention. Moreover, data analysts can develop flexible data models and create integrated analytics visualizations, which significantly enhances the overall experience of utilizing data. Ultimately, this all-encompassing analytics solution equips users at every tier to effectively leverage data for informed decision-making and strategic growth. This empowerment cultivates a culture of data-driven insights across the organization.
What is Anzo?
Anzo emerges as a groundbreaking platform focused on data discovery and integration, allowing users to seamlessly find, connect, and combine any enterprise data into analytics-ready datasets. Its innovative use of semantics and graph data models opens the door for a diverse range of individuals within an organization—from seasoned data scientists to novice business users—to engage in the data discovery and integration process, enabling them to build their own datasets for analysis. By leveraging graph data models, Anzo offers business users an intuitive visual representation of the enterprise's data environment, which simplifies navigation and understanding, even when faced with large, isolated, and complex datasets. The addition of semantics not only enhances the data with relevant business context but also helps users align data through shared definitions, allowing for the dynamic creation of integrated datasets that meet specific requirements. This approach promotes broader access to data and enhances its usability, cultivating a data-driven culture within organizations that encourages informed decision-making at all levels. Consequently, Anzo stands as a vital tool for enhancing collaboration and efficiency in data management across various departments.
Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
API Availability
Has API
API Availability
Has API
Pricing Information
$599 / mo
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
InAppBI
Company Location
United States
Company Website
www.inappbi.com/index.html
Company Facts
Organization Name
Cambridge Semantics
Date Founded
2007
Company Location
United States
Company Website
www.cambridgesemantics.com/product/
Categories and Features
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics
Categories and Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services