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What is TCS MasterCraft DataPlus?

Data management solutions are primarily employed by teams within large enterprises, requiring a design that emphasizes ease of use, automation, and intelligent features. It is also critical for such software to adhere to various industry regulations and data protection laws. To empower business teams to make well-informed, data-driven strategic choices, the information handled must meet high standards of adequacy, accuracy, consistency, quality, and secure access. The software advocates for a holistic approach to managing data privacy, assuring data quality, supervising test data management, enabling data analytics, and aiding in data modeling. In addition, it efficiently handles growing data volumes using a service engine-based architecture, while also catering to unique data processing requirements through a customizable function framework and a Python adapter. Furthermore, it creates a coherent governance structure that emphasizes data privacy and quality management, thereby bolstering overall data integrity. This comprehensive approach ensures that organizations can depend on this software to adapt to their ever-changing data needs, ultimately fostering enhanced operational efficiency and data reliability.

What is Data Quality on Demand?

Data plays a vital role in multiple sectors of a business, such as sales, marketing, and finance. To fully leverage this data, it's important to maintain its integrity, protect it, and manage it effectively throughout its entire lifecycle. At Uniserv, we believe that data quality is a core principle of our identity and the services we offer. Our customized solutions convert your customer master data into a crucial asset for your business. The Data Quality Service Hub ensures that your customer data remains of the highest quality across all locations within your organization, including those overseas. We offer services that align your address information with international standards, utilizing the best reference data available. Furthermore, we validate email addresses, phone numbers, and banking information with meticulous attention to detail. If your data has duplicate entries, we can quickly pinpoint them according to your defined business requirements. Often, the identified duplicates can be merged automatically using predefined rules or categorized for manual assessment, which promotes an efficient data management workflow that boosts operational productivity. This thorough strategy for ensuring data quality not only aids in compliance but also builds trust and credibility in your customer relationships, ultimately leading to stronger business outcomes. An unwavering commitment to data quality fosters a culture of accountability within the organization, encouraging all departments to prioritize accurate data handling.

Media

Media

Integrations Supported

Actifio
Adenza
Adobe Advertising Cloud
Amazon Web Services (AWS)
Apigee
Avaya Aura
Blueprint
Boomi
Creatio
Freshdesk
Google Cloud Platform
Hitachi Content Intelligence
IBM Cloud
Infor CRM
Juniper Identity Management Service
MongoDB
MuleSoft Anypoint Platform
Salesforce

Integrations Supported

SAP Store

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Tata Consultancy Services

Date Founded

1968

Company Location

India

Company Website

www.tcs.com/mastercraft/dataplus

Company Facts

Organization Name

Uniserv

Date Founded

1969

Company Location

Germany

Company Website

www.uniserv.com/en/business-cases/customer-data-management/data-quality/

Categories and Features

Data Management

Not specified

Data Masking

Not specified

Data Quality

Not specified

Test Data Management

Not specified

Categories and Features

Data Quality

Data Deduplication

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