Gain the Ability to Harness Data and AI for Smarter Decisions and Greater Automation

Modernize your data estate and operations and get equipped with capabilities that allow

efficient and effective leverage of analytics and data.
Areas where we can help

Modern Data Foundation

Modern BI & Analytics Foundation

Data Operations

BI/GenBI & Reporting (Including Regulatory Reports)

Interoperability

ML Model Development and Training

Compliance (High Quality Data Compliance)

Areas where we can help
Modern Data Foundation

Effectively acquire, transform, integrate, store, and consume enterprise-wide data by establishing a cloud-native, resilient and secure data estate.

Areas where we can help

Modern Data Foundation

Effectively acquire, transform, integrate, store, and consume enterprise-wide data by establishing a cloud-native, resilient and secure data estate

Areas where we can help

Data integration architecture:

Leverage automated integration of data from internal and external sources with robust pipelines

High performance data architecture:

Build your infrastructure on cutting-edge technologies and architecture best practices, to meet evolving needs.

Master Data Management:

Establish a single source of truth for your multi-domain data to get a unified, trusted business view.

Data security, quality and Integrity:

Define and implement rules, processes and governance mechanisms to ensure right quality data is available securely for data consumers..

Modern BI & Analytics Foundation

Efficiently and swiftly explore and analyze enterprise data to enable data-driven insights and smarter decisions with a robust and flexible infrastructure.

Areas where we can help

Data Integration Architecture:

Leverage data from any source (via simple JIT, enterprise-wide) to surface metrics and business insights

High Performance Warehousing Architecture (EDW/BDW):

Get a complete view and achieve efficient data management while meeting operational and analytical data needs of individual service lines, functions, and business processes

Data Security, Quality and Integrity:

Ensure relevant data of right quality is available securely to power BI, analytics, reporting needs

BI & Analytics Foundation:

Develop a foundation to democratize data analysis, leverage BI at scale, and enable GenBI capabilities

Data Operations

Effectively run and efficiently operate your enterprise data infrastructure to ensure its stability, availability, security, and resource-efficiency for the business.

Areas where we can help

Running and Operation of Data and Analytics Foundation

Helpdesk, support, and incident management

Performance optimization

Cost management and capacity planning

User administration and workspace management

Data security and encryption

Backup & recovery

Maintenance and Support

For implemented pipelines, reports and daily process enhancements, production support, and defect fixes

MLOps

Manage and govern the development, utilization, and optimization of ML models

BI/GenBI & Reporting

Helping enterprise users to derive insights from data to drive business performance as well as to meet reporting needs with cutting-edge industry-specific BI capabilities and assets.

Areas where we can help

Pre-built BI Semantic Models:

Enable speed-to-insights and relevant analytics

KPI and Metrics Library:

Accelerate the productivity of BI, analytics and reports development with a library of granularly pre-defined KPI’s/metrics

Pre-Built Dashboard Templates:

Leverage dashboards that can be customized to provide tailored insights

Interoperability

Securely share reliable information with partners, customers, regulators, third-parties in appropriate formats to drive industry-compliant communications, efficiency, and higher-quality service offerings.

Areas where we can help

Adopt Industry Standards:

Leverage industry-standard data formats and schemas to facilitate seamless data exchange and integration

Data Sharing Solutions

Data Exchange:

Share data internally and externally with high-performance (SFTP, REST, WebSockets, etc.) mechanisms

Data API:

Build, use and manage APIs to securely share data with third party partners, regulators and peers

Report Sharing Solutions:

Automate the distribution of reports between organizations with rigid controls

Data Compliance

Govern and manage security, compliance and access of all your enterprise data to meet regulatory standards with robust compliance monitoring

Areas where we can help

Compliance management:

Maintain and update policies, procedures, and practices for regulatory compliance (GDPR, CCPA, GLB, etc.) and privacy regulations

Data Security:

Implement role-based access controls for sensitive data and encryption to protect data at rest and in transit

Data Retention and Disposal Tools:

Automate data retention schedules and ensure timely data disposal, complying with legal requirements

Compliance Audits & Reporting:

Track data access, changes, and usage in real-time across the organization to provide detailed audit trails for compliance reporting

Continuous Monitoring and Improvement:

Track compliance with automated tools, assessments, and implement improvements based on audit findings and regulatory changes

ML Model Development and Training

End-to-end solution approach from defining the analytics problem statement, to assembling and exploring the required data, to designing and operationalizing the ML solution

Areas where we can help

AI/ML Use Case Discovery:

We work with your leadership to understand your business goals, identify and prioritize high-value use cases across your organization and develop a roadmap

AI/ML Model development and training:

Creating Modelling Inputs:

Acquire and process high quality data, design and engineer new features

Model Build:

Select appropriate ML models suited for the use case, leverage training datasets to train the models

Model Validation:

Use evaluation metrics to measure the model efficacy, refine and fine tune the model through experimentation for optimal performance

Model Implementation:

Adapt models with implementation constraints and business rules and define requirements for model deployment