Data modernization Services
Your data exists across systems but is hard to access, trust, or use. Modernize how data is structured, stored, and moved so it becomes usable across your business.
What we enable
Data modernization removes fragmentation and inconsistency, making data easier to access, trust, and use across systems and workflows.
What we enable
Data modernization removes fragmentation and inconsistency, making data easier to access, trust, and use across systems and workflows.
01
Access data without delays
Get reliable data when needed without manual extraction or workarounds.
02
Ensure consistent data across systems
Remove duplication and mismatches across sources and applications.
03
Improve data quality and trust
Standardize and validate data so it can be used confidently in decisions and systems.
04
Support real-time and batch use cases
Enable both real-time access and structured data pipelines based on your needs.
Built across financial and regulated environments
Alternative asset management
Specialty lending
Wealth management
PE-backed platforms
Experience with clients backed by
Built across financial and regulated environments
Experience with clients backed by
What we do
We restructure how your data is organized, stored, and accessed so it becomes reliable and usable across systems.
What we do
We restructure how your data is organized, stored, and accessed so it becomes reliable and usable across systems.
Unify data sources
Bring together data from multiple systems into a consistent structure.
Standardize data models
Define clear schemas and formats for reliable usage across applications.
Build scalable data pipelines
Enable consistent data movement across systems in real time or batch.
How the system works
We improve how data flows across systems so it is consistent, accessible, and ready for use.
Assess current data landscape
Identify fragmentation, inconsistencies, and access limitations.
Restructure data layers
Organize storage, processing, and access layers for clarity and scalability.
Enable consistent data flow
Ensure reliable movement of data across systems and pipelines.
Prepare for advanced use cases
Make data ready for analytics, reporting, and AI applications.
Assess current data landscape
Identify fragmentation, inconsistencies, and access limitations.
Restructure data layers
Organize storage, processing, and access layers for clarity and scalability.
Enable consistent data flow
Ensure reliable movement of data across systems and pipelines.
Prepare for advanced use cases
Make data ready for analytics, reporting, and AI applications.
Assess current data landscape
Identify fragmentation, inconsistencies, and access limitations.
Restructure data layers
Organize storage, processing, and access layers for clarity and scalability.
Enable consistent data flow
Ensure reliable movement of data across systems and pipelines.
Prepare for advanced use cases
Make data ready for analytics, reporting, and AI applications.
Assess current data landscape
Identify fragmentation, inconsistencies, and access limitations.
Restructure data layers
Organize storage, processing, and access layers for clarity and scalability.
Enable consistent data flow
Ensure reliable movement of data across systems and pipelines.
Prepare for advanced use cases
Make data ready for analytics, reporting, and AI applications.
Building Data-First AI in Production for regulated and data-intensive industries?
Assess your AI readinessHow we engage
We start with a focused discussion around where data is limiting your ability to operate or make decisions.
How we engage
We start with a focused discussion around where data is limiting your ability to operate or make decisions.
Identify where this fits
We assess which systems and datasets need modernization.
Define a clear scope
We focus on specific data layers or pipelines without disrupting everything.
Work as an extension of your team
We collaborate closely to ensure the solution works within your systems.
Start with a focused conversation
We review your data landscape and identify gaps affecting usability and access.
Identify where this fits
We assess which systems and datasets need modernization.
Define a clear scope
We focus on specific data layers or pipelines without disrupting everything.
Work as an extension of your team
We collaborate closely to ensure the solution works within your systems.
Start with a focused conversation
We review your data landscape and identify gaps affecting usability and access.
Identify where this fits
We assess which systems and datasets need modernization.
Define a clear scope
We focus on specific data layers or pipelines without disrupting everything.
PARTNER + CERTIFICATE
Recognized by Platform Leaders. Trusted in Production.
PARTNER + CERTIFICATE
Recognized by Platform Leaders. Trusted in Production.
Frequently asked questions
Data migration and modernization services relocate data from legacy systems to modern platforms while transforming architecture, improving performance, and enabling advanced capabilities. Services include migration planning, data profiling, ETL/ELT transformation, cloud platform implementation, quality validation, security enhancement, and optimization ensuring successful transitions with minimal business disruption.
Services handle database migrations (SQL to NoSQL, on-premises to cloud), data warehouse modernization, mainframe data migration, application data transfers, cloud-to-cloud migrations, legacy system decommissioning, data lake implementations, hybrid architecture deployments, and consolidation projects reducing infrastructure complexity and costs.
Services ensure integrity through comprehensive data profiling, validation rules, automated quality checks, reconciliation processes, checksums verification, pre-migration testing, parallel validation, rollback procedures, incremental migration strategies, post-migration audits, and extensive testing protocols guaranteeing complete, accurate data transfer without loss.
Services address incompatible schemas, data quality issues, downtime constraints, legacy format conversions, security and compliance requirements, performance optimization, application dependencies, user access management, business continuity needs, and risk mitigation ensuring smooth transitions from outdated systems to modern platforms.
Timelines vary by data volume and complexity. Simple migrations complete in two to four months. Mid-sized enterprise projects require four to eight months. Complex large-scale migrations involving petabytes, multiple legacy systems, intricate dependencies, and minimal downtime requirements span nine to eighteen months.
Costs depend on data volume and complexity. Small migration projects start at $50,000 to $150,000. Mid-sized enterprise migrations range from $200,000 to $600,000. Large-scale modernization programs involving extensive data estates, complex transformations, cloud infrastructure, and comprehensive validation exceed $1 million for complete implementation.
Turn bottlenecks into running systems
Pick a process where work is slowing down. We’ll help you turn it into a system that runs with minimal manual effort.
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