data-driven decisions made simple and effective with analytics as a service
Book a demo Analytics as a service (AaaS)
Infosys BPM analytics as a service (AaaS) gives global enterprises a managed analytics operating model that combines cloud-based data platforms, AI-enabled insights, and consumption-based commercial structures into a single integrated service. We help enterprises shift from product-centric, in-house analytics teams to a flexible, services-based analytics consumption model that scales with business need.
Powered by Infosys Topaz, our AI-first framework, our AaaS delivery integrates advanced analytics technologies, machine learning, and predictive modeling with enterprise-grade data governance, security, and regulatory compliance. Enterprises access real-time insights, forecast trends, and optimize operations through a single managed analytics layer, reducing the operational burden of building and running analytics in-house while accelerating time to business value across reporting, business intelligence, and predictive use cases.
Transform your business with analytics as a service
unlocking value with our analytics as a service
- Our analytics as a service operating model enables clients to establish a robust reporting and analytics infrastructure. This infrastructure serves as the backbone for business intelligence and data-driven decision-making.
- By leveraging cloud-based platforms and analytics tools, organizations can quickly deploy preconfigured analytics solutions. These solutions are scalable and AI/ML-ready.
- The analytics operating model evolves towards a services-based approach, shifting from a product-centric mindset to a flexible consumption model that incorporates data sources.
- As one of the leading enterprise analytics as a service providers, we ensure seamless information flow and effective data analysis. This ensures that siloed data, which often leads to multiple sources of truth and security risks, is transformed into valuable insights using data warehousing techniques.
Our analytics as a service business model empowers organizations to make informed business decisions based on big data and predictive analytics, shifting from capital-intensive in-house analytics to a scalable consumption-based model with measurable business outcomes. Whether optimizing processes, improving efficiency, or identifying cost-saving opportunities, the insights derived from AaaS drive value.
Analytics as a service capabilities across the enterprise
Infosys BPM analytics as a service is delivered through an integrated capability framework that spans the full analytics value chain, from data ingestion to insight delivery. Our managed analytics operating model is designed for enterprises that want flexible, services-based analytics consumption without the cost and complexity of building in-house analytics teams.
Reporting and business intelligence as a service
Cloud-based reporting infrastructure, self-service BI dashboards, and standardized executive reporting frameworks deployed and managed as a service. Designed for enterprises that need consistent, scalable reporting across business units without the operational burden of running BI platforms internally.
Advanced analytics and AI as a service
AI-enabled analytics including machine learning models, predictive modeling, anomaly detection, and pattern recognition delivered as part of an integrated analytics service. Powered by Infosys Topaz, with operational deployment across customer analytics, supply chain intelligence, financial forecasting, and operational analytics use cases.
Data engineering and platform operations
End-to-end data engineering services including data ingestion, cleansing, warehousing, and platform operations. We manage the underlying data infrastructure, including cloud-based data lakes and analytics platforms, so enterprise teams can focus on insight consumption rather than platform maintenance.
Analytics governance and compliance
Enterprise-grade data governance covering data quality management, security controls, access management, and regulatory compliance (GDPR, CCPA, industry-specific requirements). Built into the analytics service rather than added as a separate layer, supporting enterprises in regulated sectors including BFSI, healthcare, and insurance.
Insights
Challenges & solutions - analytics as a service business model
Analytics as a service is most strategically valuable when enterprises face one of three conditions: scaling analytics demand faster than in-house teams can grow, modernizing legacy reporting and BI infrastructure without large capital investment, or extending analytics into new use cases such as predictive AI and real-time operational analytics that require specialized capabilities. Building or expanding in-house analytics remains the right choice when analytics is a core competitive differentiator or involves highly proprietary data. Infosys BPM analytics as a service is designed for enterprises in the first three scenarios, complementing in-house analytics rather than replacing strategic analytics capabilities.
Enterprises evaluating analytics as a service providers should assess five dimensions beyond surface capability claims: data infrastructure depth (cloud-native platforms versus legacy stacks), AI and machine learning maturity (operational deployments versus pilot-stage capability), governance and regulatory framework (enterprise-grade versus ad-hoc), commercial model flexibility (consumption-based versus fixed), and transition rigor (structured methodology versus ad-hoc handover). The right AaaS provider is not necessarily the one with the largest analytics workforce, but the one whose operating model aligns with the enterprise's analytics maturity, vertical regulatory requirements, and commercial structure preferences. Infosys BPM analytics as a service is built on cloud-native platforms, AI-first delivery powered by Infosys Topaz, enterprise-grade governance, flexible commercial structures, and structured transition methodologies.
An analytics as a service operating model is built on three integrated layers: data infrastructure including cloud-based data lakes and analytics platforms, analytics capability including AI and machine learning models, predictive analytics, reporting and business intelligence tools, and managed delivery including operational teams running analytics workflows as a service. Enterprises consume insights through standardized interfaces such as dashboards, APIs, and reports without managing the underlying technology or operations. Infosys BPM analytics as a service operating model is powered by Infosys Topaz and integrated with enterprise-grade governance, security, and regulatory compliance.
Data security and regulatory compliance in analytics as a service depend on the provider's governance framework and the contractual structure of the engagement. Enterprises should evaluate providers on data residency controls covering where data is physically stored and processed, access management and audit capabilities, regulatory certifications including GDPR, CCPA, SOC2, and industry-specific frameworks, and incident response procedures. Infosys BPM analytics as a service includes enterprise-grade data governance with role-based access controls, encrypted communications, audit logging, and compliance frameworks built into the service rather than added as a separate layer.
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