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What is IBM InfoSphere Optim Data Privacy?

IBM InfoSphere® Optim™ Data Privacy provides an extensive range of tools aimed at effectively concealing sensitive data in non-production environments such as development, testing, quality assurance, and training. This all-in-one solution utilizes a variety of transformation techniques to substitute sensitive information with realistic, functional masked versions, thereby preserving the confidentiality of essential data. Among the masking methods employed are the use of substrings, arithmetic calculations, generation of random or sequential numbers, date manipulation, and the concatenation of data elements. Its sophisticated masking capabilities ensure that the formats remain contextually relevant and closely mimic the original data. Users are empowered to implement a wide selection of masking strategies as needed to protect personally identifiable information and sensitive corporate data across applications, databases, and reports. By leveraging these data masking functionalities, organizations can significantly reduce the risk of data exploitation by obscuring, privatizing, and safeguarding personal information shared in non-production settings, thus improving data security and regulatory compliance. Furthermore, this solution not only addresses privacy concerns but also enables businesses to uphold the reliability of their operational workflows. Through these measures, companies can navigate the complexities of data privacy with greater ease.

What is IBM InfoSphere Information Analyzer?

Understanding the quality, structure, and arrangement of your data is an essential first step in making impactful business decisions. The IBM® InfoSphere® Information Analyzer, a component of the IBM InfoSphere Information Server suite, evaluates the quality and organization of data both within standalone systems and across various environments. It features a reusable library of rules that enables assessments at different tiers based on established records and patterns. Additionally, it assists in handling exceptions to set rules, facilitating the detection of inconsistencies, redundancies, and anomalies within the data while helping to determine the best structural arrangements. By utilizing this tool effectively, organizations can significantly enhance their data governance, leading to more informed decision-making processes. Ultimately, this capability empowers businesses to adapt more swiftly to evolving market demands.

Media

Media

Integrations Supported

Amdocs Customer Experience Suite
Hadoop
IBM Cloud
IBM Db2
IBM InfoSphere Optim
IBM Informix
JD Edwards EnterpriseOne
Oracle PeopleSoft
Oracle Siebel CRM
SQL Server

Integrations Supported

Amdocs Customer Experience Suite
Hadoop
IBM Cloud
IBM Db2
IBM InfoSphere Optim
IBM Informix
JD Edwards EnterpriseOne
Oracle PeopleSoft
Oracle Siebel CRM
SQL Server

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/il-en/products/infosphere-optim-data-privacy

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/infosphere-information-analyzer

Categories and Features

Data Privacy Management

Access Control
CCPA Compliance
Consent Management
Data Mapping
GDPR Compliance
Incident Management
PIA / DPIA
Policy Management
Risk Management
Sensitive Data Identification

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Quality

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

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