Average Ratings 28 Ratings
Average Ratings 0 Ratings
Description
Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence.
Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs.
Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.
Description
The primary obstacle in expanding AI-driven decision-making lies in the underutilization of data. IBM Cloud Pak® for Data provides a cohesive platform that integrates a data fabric, enabling seamless connection and access to isolated data, whether it resides on-premises or in various cloud environments, without necessitating data relocation. It streamlines data accessibility by automatically identifying and organizing data to present actionable knowledge assets to users, while simultaneously implementing automated policy enforcement to ensure secure usage. To further enhance the speed of insights, this platform incorporates a modern cloud data warehouse that works in harmony with existing systems. It universally enforces data privacy and usage policies across all datasets, ensuring compliance is maintained. By leveraging a high-performance cloud data warehouse, organizations can obtain insights more rapidly. Additionally, the platform empowers data scientists, developers, and analysts with a comprehensive interface to construct, deploy, and manage reliable AI models across any cloud infrastructure. Moreover, enhance your analytics capabilities with Netezza, a robust data warehouse designed for high performance and efficiency. This comprehensive approach not only accelerates decision-making but also fosters innovation across various sectors.
API Access
Has API
No
API Access
Has API
No
Integrations
Confluence
Yes
Databricks
Yes
Datamatics Trade Finance
No
Facebook
Yes
GitHub
Yes
GitLab
Yes
Gmail
Yes
IBM Control Desk
No
IBM Db2 Big SQL
No
IBM Db2 Event Store
No
Integrations
Confluence
No
Databricks
No
Datamatics Trade Finance
Yes
Facebook
No
GitHub
No
GitLab
No
Gmail
No
IBM Control Desk
Yes
IBM Db2 Big SQL
Yes
IBM Db2 Event Store
Yes
Pricing Details
$0.25/credit
Free Trial
Yes
Free Version
No
Pricing Details
$699 per month
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
Yes
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
No
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Gathr.ai
Country
United States
Website
www.gathr.ai
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/cloud-pak-for-data
Product Features
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
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No
ETL
Data Analysis
No
Data Filtering
No
Data Quality Control
No
Job Scheduling
No
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Streaming Analytics
Data Enrichment
Yes
Data Wrangling / Data Prep
Yes
Multiple Data Source Support
Yes
Process Automation
Yes
Real-time Analysis / Reporting
Yes
Visualization Dashboards
Yes
Product Features
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
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
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Predictive Analytics
AI / Machine Learning
No
Benchmarking
No
Data Blending
No
Data Mining
No
Demand Forecasting
No
For Education
No
For Healthcare
No
Modeling & Simulation
No
Sentiment Analysis
No