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ease
features
design
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ease
features
design
support

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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.

Description

Rapidly establish cloud environments tailored for spontaneous development, testing, and enhanced productivity for IT and business personnel. Mitigate the risks and expenses associated with managing your data lake by adopting robust data governance practices that include comprehensive end-to-end data lineage for business users. Achieve greater cost efficiency by providing clean, reliable, and timely data for your data lakes, data warehouses, or big data initiatives, while also consolidating applications and phasing out legacy databases. Benefit from automatic schema propagation to accelerate job creation, implement type-ahead search features, and maintain backward compatibility, all while following a design that allows for execution across varied platforms. Develop data integration workflows and enforce governance and quality standards through an intuitive design that identifies and recommends usage trends, thus enhancing user experience. Furthermore, boost visibility and information governance by facilitating complete and authoritative insights into data, backed by proof of lineage and quality, ensuring that stakeholders can make informed decisions based on accurate information. With these strategies in place, organizations can foster a more agile and data-driven culture.

Description

Conventional techniques for integrating mainframe data, such as ETL, data warehouses, and connector development, are increasingly inadequate in terms of speed, accuracy, and efficiency in today’s business landscape. As the amount of data generated and stored on mainframes continues to surge, these outdated methods fall further behind. Data virtualization emerges as the solution to bridge this growing divide, automating the accessibility of mainframe data for developers and applications alike. This approach allows organizations to discover and map their data just once, after which it can be easily virtualized and reused across various platforms. Ultimately, this capability enables your data to align with your business goals and aspirations. By leveraging data virtualization on z/OS, organizations can simplify the complexities associated with mainframe resources. Moreover, data virtualization facilitates the integration of data from numerous disparate sources into a cohesive logical repository, significantly enhancing the ability to connect mainframe information with distributed applications. This method also allows for the enrichment of mainframe data by incorporating insights from location, social media, and other external datasets, promoting a more comprehensive understanding of business dynamics.

API Access

Has API

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Screenshots View All

Integrations

Amazon S3
Apache Cassandra
Apache HBase
Apache Kafka
Cloudera
Datamatics Trade Finance
Google Cloud Storage
Hive
IBM Cloud
IBM Control Desk
IBM Db2 Big SQL
IBM Db2 Event Store
IBM InfoSphere Information Governance Catalog
IBM Netezza Performance Server
IBM Storage Software Suite
IBM WebSphere Commerce
Microsoft Azure
PayTrace

Integrations

Amazon S3
Apache Cassandra
Apache HBase
Apache Kafka
Cloudera
Datamatics Trade Finance
Google Cloud Storage
Hive
IBM Cloud
IBM Control Desk
IBM Db2 Big SQL
IBM Db2 Event Store
IBM InfoSphere Information Governance Catalog
IBM Netezza Performance Server
IBM Storage Software Suite
IBM WebSphere Commerce
Microsoft Azure
PayTrace

Integrations

Amazon S3
Apache Cassandra
Apache HBase
Apache Kafka
Cloudera
Datamatics Trade Finance
Google Cloud Storage
Hive
IBM Cloud
IBM Control Desk
IBM Db2 Big SQL
IBM Db2 Event Store
IBM InfoSphere Information Governance Catalog
IBM Netezza Performance Server
IBM Storage Software Suite
IBM WebSphere Commerce
Microsoft Azure
PayTrace

Pricing Details

$699 per month
Free Trial
Free Version

Pricing Details

$16,500 per month
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/cloud-pak-for-data

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/infosphere-information-server-enterprise

Vendor Details

Company Name

Rocket

Founded

1990

Country

United States

Website

www.rocketsoftware.com/product-categories/data-virtualization

Product Features

Big Data

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

Data Fabric

Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Predictive Analytics

AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis

Product Features

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

Product Features

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