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What is IBM DataStage?

Accelerate the development of AI innovations with the cloud-native data integration solutions provided by IBM Cloud Pak for Data. With AI-enhanced data integration functionalities available from any location, the impact of your AI and analytics initiatives is closely tied to the caliber of the underlying data. Leveraging a contemporary container-based framework, IBM® DataStage® within IBM Cloud Pak® for Data guarantees the provision of high-quality data. This offering combines exceptional data integration with DataOps, governance, and analytics into a cohesive data and AI ecosystem. By streamlining administrative processes, it contributes to a reduction in total cost of ownership (TCO). The platform's AI-driven design accelerators, in conjunction with readily available integrations for DataOps and data science services, significantly expedite the pace of AI development. Moreover, its capabilities for parallel processing and multicloud integration facilitate the delivery of consistent data across extensive hybrid or multicloud environments. Additionally, the IBM Cloud Pak for Data platform allows for the effective management of the complete data and analytics lifecycle, incorporating a range of services such as data science, event messaging, data virtualization, and data warehousing, all supported by a parallel engine and automated load balancing. This all-encompassing strategy equips your organization to remain at the forefront of the swiftly changing data and AI landscape, ensuring that you can adapt and thrive in a competitive market.

What is Ab Initio?

Data is increasingly sourced from a variety of channels, leading to a surge in both its quantity and complexity. Hidden within this vast pool of information lies a wealth of knowledge and insights, rich with untapped possibilities. However, to unlock this potential, it is essential that data informs every decision and action undertaken by the organization continuously. As businesses progress, so too does the data, giving rise to fresh insights and understanding, which fosters an ongoing cycle of learning and evolution. Industries such as financial services, healthcare, telecommunications, manufacturing, transportation, and entertainment are capitalizing on this opportunity to innovate. The path to achieving success can be both challenging and thrilling. Realizing this success necessitates exceptional speed and agility in interpreting, managing, and processing the ever-increasing volumes of dynamic data. To address these challenges, organizations must implement a comprehensive data platform that supports automation and self-service, one that thrives under constant change and adapts to new challenges while addressing complex data processing and management needs. This innovative strategy not only boosts operational efficiency but also equips organizations to sustain their competitive edge in an environment that is continuously evolving. Ultimately, the ability to effectively leverage data can determine an organization's trajectory in today's fast-paced market.

Media

Media

Integrations Supported

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
Origina
Pantomath
Stonebranch

Integrations Supported

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
Origina
Pantomath
Stonebranch

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

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/infosphere-datastage

Company Facts

Organization Name

Ab Initio

Date Founded

1995

Company Location

United States

Company Website

www.abinitio.com/en/

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

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

Categories and 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

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