Drive growth and enhance data storytelling with
intelligent solutions and data-driven insights

As analytics becomes more widely used for competitive advantage and growth, there is a greater focus on privacy, bias removal, and explainability. Ethical considerations such as discrimination and responsible data use are also gaining attention. Hybrid platforms that combine cloud-based and on-premise analytics are becoming more popular due to their scalability and flexibility.

However, only a small percentage of models are successfully transitioned into production. To improve this, companies with legacy systems and technical debt may need help implementing modern analytics solutions that integrate with existing business processes. Maintaining scalability and performance while processing large amounts of data can be challenging, and using sensitive data for analytics raises concerns about security and privacy.

Virtusa can assist in enhancing data storytelling capabilities, improving scalability and flexibility throughout the analytics development process, and pushing the boundaries of what is currently possible while remaining within the framework of Information security and regulations.

Our capabilities
Data Analytics Services - Capabilities
  • Data and analytics strategy and consulting
    We work with clients to understand their business goals and challenges so we can develop a customized strategy and roadmap to help them implement machine learning solutions. 

  • Platform-based approach for data and analytics
    Industry-specific and agnostic platforms provide a standardized, streamlined, and cost-effective way of building data and analytics solutions for accelerated time to delivery.

  • Technology agnostic solutions
    Our strong partnerships with multiple partners such as AWS, Google Cloud, Azure, Tableau, SAS, and IBM enable us to deliver solutions across multiple technology stacks. 

Our accelerators, or production models used to address common errors during production for artificial intelligence and machine learning (AI/ML) operations, ensure that models are monitored in production.

Adopt a cloud and platform-based analytics approach to reduce costs and increase efficiency

  • Adopt a cloud-based data storage and analytics approach to enable fast and easy access to data and reduce infrastructure costs.
  • Establish a clear data governance framework to ensure data quality, security, and compliance.
  • Create a single source of truth by establishing a master data management strategy and ensuring that the data is accurate, complete, and consistent across all systems. 
  • Leverage data visualization tools to help stakeholders quickly and easily understand insights and trends. 
  • Consider adopting a platform-based analytics and insights implementation approach to provide a consistent and scalable infrastructure for development, deployment, and management. 
  • Build and leverage reusable assets, such as data sets, to streamline, develop and accelerate time to market. This will also help reduce costs and increase analytics and insights development efficiency. 


Ready to begin your Analytics adoption journey?

Speak to an expert, request an assessment, demo our solutions.