Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Information flows in from various sources, increasing in both volume and intricacy. Within this information lies valuable knowledge and insights brimming with potential. This potential can only be fully harnessed when it influences every decision and action taken by the organization in real-time. As the landscape of business evolves, the data itself transforms, yielding fresh knowledge and insights. This establishes a continuous cycle of learning and adaptation. Sectors as diverse as finance, healthcare, telecommunications, manufacturing, transportation, and entertainment have acknowledged the opportunities this presents. The journey to capitalize on these opportunities is both formidable and exhilarating. Achieving success requires unprecedented levels of speed and agility in comprehending, managing, and processing vast quantities of ever-evolving data. For complex organizations to thrive, they need a high-performance data platform designed for automation and self-service, capable of flourishing amidst change and adjusting to new circumstances, while also addressing the most challenging data processing and management issues. In this rapidly evolving environment, organizations must commit to investing in innovative solutions that empower them to navigate the complexities of their data landscapes effectively.
Description
Boost the pace of AI innovation through cloud-native data integration offered by IBM Cloud Pak for Data. With AI-driven data integration capabilities accessible from anywhere, the effectiveness of your AI and analytics is directly linked to the quality of the data supporting them. Utilizing a modern container-based architecture, IBM® DataStage® for IBM Cloud Pak® for Data ensures the delivery of superior data. This solution merges top-tier data integration with DataOps, governance, and analytics within a unified data and AI platform. By automating administrative tasks, it helps in lowering total cost of ownership (TCO). The platform's AI-based design accelerators, along with ready-to-use integrations with DataOps and data science services, significantly hasten AI advancements. Furthermore, its parallelism and multicloud integration capabilities enable the delivery of reliable data on a large scale across diverse hybrid or multicloud settings. Additionally, you can efficiently manage the entire data and analytics lifecycle on the IBM Cloud Pak for Data platform, which encompasses a variety of services such as data science, event messaging, data virtualization, and data warehousing, all bolstered by a parallel engine and automated load balancing features. This comprehensive approach ensures that your organization stays ahead in the rapidly evolving landscape of data and AI.
API Access
Has API
API Access
Has API
Integrations
ActiveBatch Workload Automation
BMC AMI Ops Automation for Capping
DataHawk
FairCom DB
FairCom EDGE
IBM Cloud Pak for Applications
IBM Watson Studio
IRI FieldShield
Impetus
MettleCI
Integrations
ActiveBatch Workload Automation
BMC AMI Ops Automation for Capping
DataHawk
FairCom DB
FairCom EDGE
IBM Cloud Pak for Applications
IBM Watson Studio
IRI FieldShield
Impetus
MettleCI
Pricing Details
No price information available.
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
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
Vendor Details
Company Name
Ab Initio
Founded
1995
Country
United States
Website
www.abinitio.com/en/
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/infosphere-datastage
Product Features
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
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 Lineage
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control