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What is IBM InfoSphere Optim?

Proper management of data throughout its entire lifecycle is crucial for organizations to meet their business goals while reducing potential risks. Archiving data from outdated applications and historical transaction records is vital to ensure ongoing access for compliance inquiries and reporting purposes. By distributing data across different applications, databases, operating systems, and hardware, organizations can improve the security of their testing environments, accelerate release cycles, and decrease expenses. Failing to implement effective data archiving can lead to significant degradation in the performance of essential enterprise systems. Tackling data growth directly at its origin not only enhances efficiency but also minimizes the risks associated with long-term management of structured data. Moreover, it is important to protect unstructured data within testing, development, and analytics settings throughout the organization to preserve operational integrity. The lack of a solid data archiving strategy can severely impact the functionality of critical business systems and hinder overall success. Consequently, taking proactive measures to manage data effectively is fundamental for cultivating a more agile, resilient, and competitive enterprise in today's fast-paced business landscape.

What is BiG EVAL?

The BiG EVAL solution platform provides powerful software tools that are crucial for maintaining and improving data quality throughout every stage of the information lifecycle. Constructed on a solid code framework, BiG EVAL's software for data quality management and testing ensures high efficiency and adaptability for thorough data validation. The functionalities of this platform are the result of real-world insights gathered through partnerships with clients. Upholding superior data quality across the entirety of your information's lifecycle is essential for effective data governance, which significantly influences the business value extracted from that data. To support this objective, the automation tool BiG EVAL DQM plays a vital role in managing all facets of data quality. Ongoing quality evaluations verify the integrity of your organization's data, providing useful quality metrics while helping to tackle any emerging quality issues. Furthermore, BiG EVAL DTA enhances the automation of testing activities within your data-driven initiatives, further simplifying the entire process. By implementing these solutions, organizations can effectively enhance the integrity and dependability of their data assets, leading to improved decision-making and operational efficiency. Ultimately, strong data quality management not only safeguards the data but also enriches the overall business strategy.

Media

Media

Integrations Supported

Aster SQL-GR
IBM ILOG CPLEX Optimization Studio
IBM InfoSphere Optim Data Privacy
Kylo
SAP Cloud Platform
Teradata VantageCloud

Integrations Supported

Aster SQL-GR
IBM ILOG CPLEX Optimization Studio
IBM InfoSphere Optim Data Privacy
Kylo
SAP Cloud Platform
Teradata VantageCloud

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/analytics/optim

Company Facts

Organization Name

BiG EVAL

Date Founded

2010

Company Location

Switzerland

Company Website

bigeval.com/platform/

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

Categories and Features

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

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