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What is Enterprise Enabler?

Enterprise Enabler consolidates diverse information from multiple sources and fragmented data sets into a single, cohesive platform; this encompasses data stored in the cloud, scattered across standalone databases, kept on various instruments, residing in Big Data repositories, or found within numerous spreadsheets and documents. By facilitating seamless integration of all your data, it equips you to make prompt and informed business decisions. The system constructs logical representations of data from its original sources, allowing you to effectively reuse, configure, test, deploy, and monitor everything within one unified environment. This capability enables you to analyze your business data as events progress, which aids in optimizing asset utilization, lowering costs, and refining your business processes. Notably, our deployment timeline is generally 50-90% faster, ensuring that your data sources are interconnected and functioning in a remarkably short period, thus supporting real-time decision-making based on the latest available information. With this innovative solution, organizations can boost collaboration and efficiency, resulting in enhanced overall performance and a competitive edge in the marketplace. Additionally, this strategic integration fosters a culture of data-driven insights, empowering teams to innovate and adapt swiftly to market changes.

What is Conduit?

Effortlessly align data across your operational systems using a versatile, event-driven strategy that integrates smoothly with your existing workflow while reducing dependencies. Simplify the complex multi-step tasks you face by simply downloading the binary to kickstart your development process. Conduit pipelines continuously track changes in databases, data warehouses, and other sources, allowing your data applications to react to these updates in real-time. With Conduit connectors, transferring data to and from any necessary production datastore is a breeze. If you encounter a datastore that doesn't meet your needs, the intuitive SDK allows you to enhance Conduit to fit your requirements. You can choose to deploy it as an independent service or incorporate it into your current infrastructure, ensuring peak performance and adaptability. This level of flexibility not only streamlines your data synchronization but also empowers your organization to meet its unique data management needs effectively. With the right tools at your disposal, your data operations can achieve new heights of efficiency.

Media

Media

Integrations Supported

Amazon S3
Apache Kafka
HubSpot Customer Platform
PostgreSQL

Integrations Supported

Amazon S3
Apache Kafka
HubSpot Customer Platform
PostgreSQL

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

Stone Bond Technologies

Date Founded

2002

Company Location

United States

Company Website

stonebond.com

Company Facts

Organization Name

Conduit

Company Website

www.conduit.io

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

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

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Integration

Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services

Master Data Management

Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization

Categories and Features

Integration

Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services

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