Big Data Assurance: An Approach Based on Service-Level Agreements

Area of Science:

• Computer Science
• Information Systems

Background:

• Big data management is essential for enterprise competitiveness and optimization.
• Effective analysis of enterprise production data can improve management, customer relations, and reduce costs.
• Ensuring the correctness of big data pipelines, especially cloud-based services, is a significant challenge.

Purpose of the Study:

• To define an assurance solution for big data pipelines.
• To ensure big data pipelines comply with legal and user requirements.
• To facilitate the correct deployment and continuous refinement of big data pipelines.

Main Methods:

• Development of an assurance solution based on service-level agreements (SLAs).
• Implementation of a semi-automatic approach for requirement definition and negotiation.
• Focus on continuous refinement of service terms for big data provision.

Main Results:

• A framework for assuring big data pipeline correctness is proposed.
• The solution supports users from requirement specification to service negotiation and ongoing management.
• The approach aims to guarantee compliance with both legal mandates and user expectations.

Conclusions:

• Assurance techniques are vital for the reliable operation of big data pipelines.
• Service-level agreements provide a robust mechanism for ensuring big data pipeline compliance.
• The proposed semi-automatic approach enhances the management and trustworthiness of cloud-based big data services.