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Average Ratings 0 Ratings
Description
Arundo Enterprise presents a versatile and modular software suite designed for the development of data products tailored for individuals. By linking real-time data with machine learning and various analytical frameworks, we ensure that the outcomes of these models directly inform business strategies. The Arundo Edge Agent facilitates industrial connectivity and analytics, even in harsh, remote, or non-connected settings. With Arundo Composer, data scientists can effortlessly deploy desktop analytical models into the Arundo Fabric cloud environment using just one command. Additionally, Composer empowers organizations to create and manage live data streams, seamlessly integrating them with existing data models. Serving as the central cloud-based hub, Arundo Fabric supports the management of deployed machine learning models, data streams, and edge agent oversight while offering streamlined access to further applications. Arundo's impressive range of SaaS products is designed to maximize return on investment, and each solution comes equipped with a fundamental functionality that capitalizes on the inherent strengths of Arundo Enterprise. The comprehensive nature of these offerings ensures that companies can leverage data more effectively to drive decision-making and innovation.
Description
Begin your top-down evaluation with a comprehensive view of a sample Data Platform, allowing you to navigate through different areas and uncover their connections to various organizational data. From the transformation of a supply chain's business model to the implementation of Enterprise Data Platform strategies in a banking institution, there are numerous real-world examples demonstrating the effectiveness of Indyco as a data modeling tool. This initiative significantly bolstered the data culture within a prominent player in the food and agriculture sector in Italy, ultimately facilitating the advent of self-service reporting. Business users began engaging with the Conceptual Model displayed on a large screen, collaborating with IT teams during co-design sessions focused on refining their Data Platform. Additionally, a bank successfully established best practices for Data Platform design by utilizing Indyco, which included elements such as conceptual modeling, automated documentation, and the creation of a business glossary. Thus, the integration of these practices not only streamlined processes but also fostered an environment where data-driven decision-making could thrive.
API Access
Has API
No
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
Arundo
Founded
2015
Country
Norway
Website
arundo.com
Vendor Details
Company Name
Indyco
Founded
2013
Country
Italy
Website
www.indyco.com
Product Features
Big Data
Collaboration
Yes
Data Blends
Yes
Data Cleansing
Yes
Data Mining
Yes
Data Visualization
Yes
Data Warehousing
Yes
High Volume Processing
Yes
No-Code Sandbox
Yes
Predictive Analytics
Yes
Templates
Yes
Data Analysis
Data Discovery
Yes
Data Visualization
Yes
High Volume Processing
Yes
Predictive Analytics
Yes
Regression Analysis
Yes
Sentiment Analysis
Yes
Statistical Modeling
Yes
Text Analytics
Yes
Data Fabric
Data Access Management
No
Data Analytics
No
Data Collaboration
No
Data Lineage Tools
No
Data Networking / Connecting
No
Metadata Functionality
No
No Data Redundancy
No
Persistent Data Management
No
Product Features
Big Data
Collaboration
Yes
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
Yes
Data Warehousing
Yes
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No