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Digital Transformation In IndustryTop 10 Best Data Modernization Services of 2026
Editorial roundup comparing data modernization services from Hexaware, Infosys, and Deloitte for teams planning modernization options and tradeoffs.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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Hexaware is the best pick for large and regulated enterprises modernizing legacy data platforms because its proprietary modernization assets pair assessment and roadmap work with repeatable migration and cloud transformation workflows for complex programs, while Infosys fits when you need managed modernization across fragmented systems thanks to Cobalt’s migration-factory delivery framework and hyperscaler engineering patterns.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Hexaware
Hexaware combines a broad cloud delivery practice with proprietary modernization assets: Amaze accelerates assessment and cloud transformation, RAPID supports data platform modernization, and Tensai and RapidX extend automation into testing, engineering, and operations. This gives Hexaware a distinctive blend of advisory depth, reusable tooling, and implementation capacity for complex enterprise programs.
Best for: Large and regulated enterprises modernizing legacy databases, warehouses, lakes, or reporting environments across cloud platforms and requiring strategy, engineering, migration execution, governance, and ongoing support.
Infosys
Editor pickInfosys Cobalt combines migration factories, industry assets, and hyperscaler engineering patterns within one enterprise delivery framework.
Best for: Fits when large enterprises need managed modernization across fragmented systems, cloud environments, and regulated data estates.
Deloitte
Editor pickDeloitte’s industry-specific reference architectures paired with alliance-led cloud delivery patterns.
Best for: Fits when regulated enterprises need industry-specific modernization planning and large-scale implementation support.
Comparison Table
Hexaware
enterprise_vendorHexaware designs, builds, modernizes, and operates enterprise AI applications using generative AI engineering, proprietary software platforms, cloud services, data engineering, and industry-focused digital product development.
Hexaware combines a broad cloud delivery practice with proprietary modernization assets: Amaze accelerates assessment and cloud transformation, RAPID supports data platform modernization, and Tensai and RapidX extend automation into testing, engineering, and operations. This gives Hexaware a distinctive blend of advisory depth, reusable tooling, and implementation capacity for complex enterprise programs.
Hexaware supports modernization programs from early assessment and roadmap design through migration, platform construction, reporting, and operational support. Its delivery portfolio includes Oracle-to-AWS migrations, Cloudera-to-Azure Databricks transitions, Microsoft Fabric implementations, Snowflake enhancements, Redshift modernization, enterprise warehouse consolidation, and industry-specific analytics platforms. The provider differentiates itself through reusable frameworks and automation, including Amaze for cloud and data transformation, RAPID for data platform modernization, and Tensai and RapidX for engineering, testing, and operational acceleration.
The breadth of its cloud partnerships and delivery capabilities is a strength, but the offering is more suitable for complex enterprise programs than narrowly scoped self-service projects. A mortgage company could use Hexaware to move Oracle data to AWS RDS, automate ingestion with Glue, process large workloads with EMR and PySpark, orchestrate workflows with Step Functions, and expose optimized analytics through Redshift. Its work with Microsoft Fabric also shows practical experience improving refresh latency, validation, duplication checks, classification, deployment automation, and reporting consistency.
- +Broad coverage from data migration assessment and roadmap design through conversion, platform delivery, analytics, and managed operations.
- +Proprietary automation platforms such as Amaze and RAPID add repeatable assessment, migration, cloud transformation, and modernization workflows.
- +Strong multi-cloud and technology coverage spanning AWS, Azure, Microsoft Fabric, Snowflake, Databricks, Oracle, and Redshift.
- +Demonstrated industry experience with complex regulated data environments in finance, healthcare, insurance, energy, travel, and public-interest reporting.
- –The extensive portfolio can make solution selection and engagement scoping more complex for buyers with a narrowly defined modernization requirement.
- –Some capabilities depend on the selected hyperscaler and ecosystem components, so the final architecture may involve several third-party services.
- –The strongest evidence emphasizes large enterprise transformations, which may be excessive for smaller organizations seeking a lightweight migration.
Financial services data teams
Move Oracle mortgage data to AWS
Faster secure data access
Healthcare analytics leaders
Replace Cloudera data lake infrastructure
Cloud-native healthcare analytics
Show 2 more scenarios
Enterprise reporting teams
Centralize fragmented reporting datasets
Trusted near-real-time reporting
Hexaware builds Microsoft Fabric foundations with canonical data layers, validation controls, deployment pipelines, and standardized reporting.
Global energy operations
Modernize near-real-time commercial data
Consistent operational visibility
Hexaware consolidates inconsistent sources into Microsoft Fabric and improves ingestion latency, validation, classification, and monitoring.
Best for: Large and regulated enterprises modernizing legacy databases, warehouses, lakes, or reporting environments across cloud platforms and requiring strategy, engineering, migration execution, governance, and ongoing support.
Infosys
enterprise_vendorDigital services and consulting company offering enterprise data modernization and cloud data migration.
Infosys Cobalt combines migration factories, industry assets, and hyperscaler engineering patterns within one enterprise delivery framework.
Infosys differentiates its data modernization practice through Infosys Cobalt, industry accelerators, and large-scale engineering delivery. Services cover legacy system migration, cloud data warehouse adoption, data integration, analytics engineering, and application modernization.
Infosys also provides data quality controls, cataloging, master data management, and governance design for regulated environments. Delivery depth suits complex estates, but implementation outcomes depend heavily on assigned architects and operating-model discipline.
- +Infosys Cobalt combines cloud migration accelerators with broad hyperscaler and enterprise-application expertise.
- +Strong delivery capacity supports multi-country migrations, modernization factories, and complex integration programs.
- +Industry-specific assets address banking, healthcare, manufacturing, retail, and telecommunications data requirements.
- +Governance services cover data quality, cataloging, lineage, classification, and access-control design.
- –Large delivery structures can introduce multiple management layers and slower architectural decisions.
- –Implementation quality depends on retaining senior Infosys architects throughout complex transformation programs.
- –Custom integration work may create long-term maintenance obligations across several cloud and enterprise vendors.
- –Smaller teams may receive less attention than large accounts with broader modernization scopes.
data governance and transformation teams
Remediate master data for modernization
Cleaner downstream migration inputs
data, analytics, and platform teams
Build governed pipelines for analytics
Integrated analytics foundation
Show 2 more scenarios
enterprise technology and infrastructure teams
Migrate data platforms to cloud
Governed cloud transition
Plans and delivers migration for applications, data platforms, and legacy connections into cloud environments.
enterprise security and identity teams
Modernize identity access workflows
Coordinated access controls
Connects authentication, single sign-on, directories, and access governance across connected systems.
Best for: Fits when large enterprises need managed modernization across fragmented systems, cloud environments, and regulated data estates.
Deloitte
enterprise_vendorBig Four professional services firm offering data modernization strategy and cloud migration execution.
Deloitte’s industry-specific reference architectures paired with alliance-led cloud delivery patterns.
Deloitte supports data modernization programs that require consulting and implementation under one engagement across fragmented estates. The service coverage spans legacy data and systems migration, cloud architecture and engineering, data governance, analytics operating-model design, and analytics and integration workflows.
The catalog capabilities also include governance and workflow design for high-regulation domains like healthcare, supply chain trading, and legal operations. The tradeoff is that delivery typically relies on substantial client-side architecture decisions, process ownership, and change management.
A strong fit exists for multi-workstream programs where integration, identity, and governance must align to operating models across stakeholders. A weaker fit exists for teams seeking a narrow technical migration that does not require operating-process redesign.
- +Industry-specific reference architectures support regulated and complex operating environments.
- +Alliance coverage spans AWS, Microsoft Azure, Google Cloud, Snowflake, and Databricks.
- +Supports data governance design alongside engineering and operating-model implementation.
- +Managed services can extend transformation work after initial migration delivery.
- –Large engagement teams can create coordination overhead across strategy, engineering, and managed services.
- –Delivery quality depends heavily on the assigned partner and implementation team.
- –Enterprise delivery methods can overwhelm organizations with limited internal program management.
- –Custom work often requires sustained executive sponsorship and internal product ownership.
health system data teams
Modernize interoperability and data exchange
More consistent data exchange
marketing analytics and finance teams
Modernize modeling for planning decisions
Documented planning insights
Show 2 more scenarios
supply chain integration leaders
Modernize EDI connectivity and processes
Structured partner connectivity
Supports EDI mapping, integration architecture, and trading-partner processes across supply chain change programs.
legal operations and governance teams
Govern AI-enabled legal workflows
Clearer legal oversight
Advises legal management and governance processes for AI-enabled document workflows.
Best for: Fits when regulated enterprises need industry-specific modernization planning and large-scale implementation support.
Accenture
enterprise_vendorGlobal professional services firm providing data modernization consulting and implementation for enterprise architectures.
Accenture myNav converts workload requirements into target-cloud architecture recommendations and migration plans before implementation begins.
Accenture combines consulting, cloud engineering, and managed operations to modernize enterprise data estates at large scale. Its distinction comes from myNav for architecture planning, industry-specific operating models, and globally distributed delivery teams.
- +myNav converts workload requirements into target-cloud architecture recommendations and migration plans.
- +Industry-specific teams address banking, healthcare, retail, and public-sector data requirements.
- +Global delivery capacity supports multi-region programs with local implementation teams.
- +Managed operations extend beyond implementation into ongoing data workflow support.
- –Large service portfolios can make scope boundaries and ownership difficult to define.
- –Execution quality depends heavily on the assigned specialists and delivery structure.
- –myNav supports planning more strongly than hands-off implementation.
- –Large programs require substantial client-side architecture and governance participation.
enterprise integration teams
Modernize B2B partner connectivity
Standardized partner operations
enterprise architecture teams
Modernize governed portal data flows
Coordinated portal experiences
Show 2 more scenarios
finance transformation teams
Automate reporting and close data pipelines
More consistent close workflows
Connects finance processes to reporting, consolidation, reconciliation, planning, and audit-trail workflows.
platform engineering teams
Improve reliability for data platforms
More consistent reliability practice
Applies observability and investigation to address recurring failures and availability risks in platforms.
Best for: Fits when regulated enterprises need consulting, implementation, and ongoing operations across complex data estates.
Tata Consultancy Services
enterprise_vendorIT services and consulting firm offering enterprise data modernization and cloud migration services.
TCS MasterCraft DataPlus automates metadata discovery, profiling, lineage capture, privacy controls, and validation checks across heterogeneous sources.
Tata Consultancy Services fits large banks, insurers, retailers, and manufacturers that need one partner across assessment, engineering, and operations. TCS teams cover legacy system migration, schema conversion, cloud landing zones, application refactoring, testing, and cutover planning. MasterCraft DataPlus adds automated metadata discovery, profiling, lineage capture, validation checks, and privacy controls across heterogeneous sources.
- +MasterCraft DataPlus automates metadata discovery, profiling, lineage capture, and privacy checks.
- +Global delivery teams cover cloud, application, and operating-model changes.
- +Industry accelerators address banking, insurance, retail, and manufacturing data estates.
- +Multi-vendor cloud experience supports complex enterprise dependencies.
- –Large programs require substantial architecture governance and executive coordination.
- –Delivery consistency can vary across regions and partner teams.
- –Product-level documentation is less transparent than specialist migration software.
- –Cutovers depend on extensive client-side testing and decision gates.
Global banking groups
Consolidating regional data estates
Controlled cross-border consolidation
Insurance transformation offices
Replacing policy administration stores
Lower migration risk
Show 1 more scenario
Manufacturing data leaders
Connecting plant and corporate systems
Consistent enterprise reporting
Cloud engineering teams link operational sources with analytics workloads while preserving local deployment constraints.
Best for: Fits when multinational enterprises need coordinated modernization across legacy estates and cloud environments.
Wipro
enterprise_vendorInformation technology services company providing data modernization consulting and implementation.
FullStride Cloud Services combines cloud engineering, application modernization, and managed operations within one Wipro delivery practice.
Wipro combines legacy system migration and cloud data warehouse delivery with managed analytics operations through FullStride Cloud Services. Its delivery model joins consulting, engineering, and application support across AWS, Azure, Google Cloud, SAP, and mainframe estates.
- +Multi-cloud delivery covers AWS, Azure, and Google Cloud engineering requirements.
- +Industry accelerators address SAP, mainframe, and enterprise application modernization.
- +Managed services extend transformation work into platform operations and analytics support.
- +FullStride connects consulting, engineering, and application support under one delivery practice.
- –Engagement quality can vary across regional teams and subcontractor coordination.
- –The service model offers less standardized API and administration control than specialist platforms.
- –Large transformation programs require substantial client architecture and governance involvement.
- –Self-service provisioning and direct product configuration receive less emphasis than delivery services.
product data teams
Clean and harmonize product attributes
More consistent product information
data governance and stewardship teams
Implement metadata and lineage governance
Improved lineage visibility
Show 2 more scenarios
application portfolio leaders
Modernize legacy apps for new platforms
Modernized application workloads
Assesses and updates legacy applications using cloud engineering and modernization workstreams.
enterprise infrastructure teams
Migrate data and workloads in stages
Staged migration with support
Plans and executes data center, infrastructure, and application migrations with coordinated cutovers.
Best for: Fits when global enterprises need Wipro-led migration, cloud engineering, and ongoing managed operations across complex estates.
Genpact
enterprise_vendorProfessional services firm delivering data modernization services for intelligent operations.
Process-led modernization teams connect data engineering with finance, supply chain, and customer operations.
Genpact serves large enterprises replacing fragmented legacy estates, especially where process redesign must accompany technology work. Its delivery connects data modernization with finance, supply chain, customer service, and risk operations rather than treating infrastructure as an isolated project.
- +Process expertise connects data work to finance, supply chain, and customer operations.
- +Industry teams support regulated workflows with domain-specific controls and documentation.
- +Cloud data engineering covers migration, analytics, and AI delivery across enterprise environments.
- –Delivery quality depends on senior team allocation and client-side decision speed.
- –Public-facing API documentation and product-level provisioning controls are limited.
- –Large transformation programs require coordination across business and technology stakeholders.
enterprise data transformation leaders
Modernize the operating data estate
More unified operational data
analytics and reporting owners
Run production analytics pipelines
Reliable production reporting
Show 2 more scenarios
mortgage operations leaders
Modernize mortgage intake and controls
Standardized loan processing
Handles mortgage intake, document processing, verification, and underwriting support with quality-controlled handoffs.
accounts payable operations teams
Modernize invoice and payment workflows
Improved process control
Supports invoice capture, validation, accounts payable processing, and payment operations with stronger process control.
Best for: Fits when large enterprises need domain-led modernization across complex operations and legacy estates.
IBM Consulting
enterprise_vendorProvides cloud-native strategy, application modernization, platform engineering, and hybrid cloud consulting.
Delivery playbooks that tie hybrid cloud architecture and governance controls to modernization execution.
IBM Consulting is a data modernization services provider that differentiates through delivery programs tied to enterprise governance, cloud operating model alignment, and repeatable modernization playbooks. Core work covers legacy application refactoring, hybrid cloud data and security alignment, and productionizing AI workflows by integrating them into enterprise systems.
- +Governed delivery programs that connect data modernization to enterprise controls
- +Strong hybrid-cloud alignment across security, applications, and data teams
- +Integration-focused approach for moving AI into production workflows
- +Structured modernization planning for staged application refactors
- –Orchestrating multi-team execution adds overhead for smaller organizations
- –Tooling choices can require additional engineering effort for integration
Data governance and business ops
Governed data product collaboration across units
Reusable products with clear accountability
Enterprise transformation leaders
Staged legacy application modernization
Planned modernization with implemented changes
Show 2 more scenarios
Enterprise architecture teams
Hybrid cloud transformation across teams
Governed target architecture and execution plan
IBM Consulting aligns cloud architecture, security, and applications with data delivery plans across hybrid environments.
AI and data operations teams
Productionizing integrated AI workflows
Operational AI workflows
IBM Consulting supports moving AI and natural language use cases into operational workflows with integration and change management.
Best for: Fits when enterprises need coordinated modernization across data, apps, security, and multiple delivery teams.
Cognizant
enterprise_vendorProfessional services firm specializing in data modernization and analytics infrastructure upgrades.
Cognizant Skygrade provides automated estate discovery, dependency mapping, and migration wave planning for complex transformation programs.
Skygrade adds automated estate discovery, dependency mapping, migration wave planning, and workload tracking to large transformation programs. Cognizant combines data engineering with industry accelerators for banking, healthcare, manufacturing, and retail, reducing design work for repeatable domain patterns.
- +Skygrade supports automated discovery and migration wave planning
- +Industry accelerators cover banking, healthcare, manufacturing, and retail
- +Global delivery teams support architecture through managed operations
- +Hyperscaler partnerships support varied deployment patterns
- –Large programs can require substantial client-side architecture governance
- –Engagement quality may vary across distributed delivery teams
- –Skygrade emphasizes migration execution over standalone product usability
- –Smaller teams may receive less standardized delivery attention
Enterprise IT leaders
Legacy estate consolidation
Sequenced cutovers
Regulated data teams
Controlled reporting modernization
Controlled reporting transition
Show 1 more scenario
Global manufacturers
Plant data unification
Unified operational reporting
Engineering teams connect plant systems, enterprise applications, and analytics environments through standardized interfaces.
Best for: Fits when multinational enterprises need phased migration execution, industry-specific engineering, and managed operations across several business units.
Capgemini
enterprise_vendorTechnology services and consulting company delivering data modernization services across cloud platforms.
Sector-specific migration factories coordinate SAP, mainframe, cloud, and analytics workstreams under one delivery model.
Capgemini differentiates through large-scale delivery across SAP, mainframe, and hyperscaler estates rather than a narrow modernization product. Its teams handle legacy system migration, cloud warehouse builds, data engineering, and managed operations.
- +Deep SAP and mainframe modernization experience for complex enterprise estates.
- +Broad AWS, Azure, and Google Cloud delivery coverage.
- +Sector playbooks support regulated banking, healthcare, and public-sector workloads.
- +Managed operations extend beyond one-time migration projects.
- –Delivery quality depends heavily on the assigned consulting and engineering teams.
- –Large programs can require lengthy governance and architecture workshops.
- –Less suitable for small teams seeking a packaged self-service product.
- –Multiple subcontractors or regional units can complicate accountability.
business intelligence teams
Modernize dashboards with governed releases
Dashboards on governed data
enterprise architecture leaders
Modernize mainframe workloads with sequencing
Prioritized modernization roadmap
Show 2 more scenarios
supply chain operations leaders
Modernize data for connected execution workflows
Coordinated execution workflows
Redesigns planning, procurement, manufacturing, logistics, and execution processes across connected workstreams with governed master data.
cloud program leaders
Deliver a governed cloud migration program
Governed cloud with operations
Coordinates cloud architecture, application modernization, migration governance, and managed operations across distributed environments.
Best for: Fits when global enterprises need coordinated modernization across SAP, mainframe, cloud, and analytics estates.
Conclusion
After evaluating 10 data modernization, Hexaware stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Data Modernization
The guide ranks Hexaware, Tata Consultancy Services, Cognizant, Infosys, Accenture, Deloitte, Capgemini, IBM, Wipro, and Genpact for data modernization delivery. Hexaware leads with Amaze, RAPID, Tensai, and RapidX, while TCS, Cognizant, and Infosys provide distinct automation and enterprise migration frameworks.
The comparison emphasizes migration execution, cloud architecture, automation, governance, industry coverage, and managed operations. IBM favors DataStage and Cloud Pak for Data, while Genpact connects data engineering with finance, supply chain, and customer operations.
What Data Modernization Services Cover
Data modernization replaces or restructures legacy databases, warehouses, lakes, and reporting environments for cloud, hybrid, or multi-cloud architectures. Projects commonly include estate assessment, schema conversion, data migration, platform engineering, integration, testing, cutover planning, and ongoing operations.
Hexaware combines assessment and migration automation through Amaze and RAPID, while Tata Consultancy Services uses MasterCraft DataPlus for metadata discovery, profiling, lineage capture, privacy controls, and validation checks. These capabilities distinguish providers by their automation depth, governance controls, migration planning, and ability to coordinate complex delivery teams.
Capabilities That Separate Data Modernization Providers
Migration assessment, target-platform design, conversion engineering, testing, and managed operations determine whether a provider can move complex estates beyond isolated pilot projects. Governance controls also affect how teams validate sources, protect sensitive records, and manage post-migration changes.
Assessment and migration automation
Hexaware combines Amaze for assessment and cloud transformation with RAPID for data platform modernization. Tata Consultancy Services uses MasterCraft DataPlus for metadata discovery, profiling, lineage capture, privacy checks, and validation.
Estate discovery and migration sequencing
Cognizant Skygrade maps dependencies and organizes migration waves for complex estates. Infosys Cobalt combines migration factories with hyperscaler engineering patterns and enterprise application expertise.
Target architecture planning
Accenture myNav translates workload requirements into target-cloud architecture recommendations before implementation. Deloitte applies industry-specific reference architectures with delivery patterns across AWS, Microsoft Azure, Google Cloud, Snowflake, and Databricks.
Transformation execution and platform controls
IBM DataStage distributes transformation jobs across parallel nodes and preserves reusable stage-based designs. Cloud Pak for Data adds catalog, lineage, quality, and policy controls across heterogeneous sources.
Operating-model and managed-service coverage
Capgemini coordinates SAP, mainframe, cloud, and analytics workstreams through sector-specific migration factories. Wipro FullStride combines cloud engineering, application modernization, and managed operations, while Genpact connects data engineering with finance, supply chain, and customer operations.
How to Match a Provider to the Modernization Program
The decision depends on estate complexity, required delivery control, target architecture, and the internal team available to govern the work. A provider with strong assessment tooling may suit a large migration inventory, while a sector-specific factory may matter more for SAP, mainframe, or regulated workflows.
Choose automation-led or factory-led delivery
Select Hexaware when reusable assets such as Amaze, RAPID, Tensai, and RapidX should drive assessment, engineering, testing, and operations. Select Capgemini when coordinated SAP, mainframe, cloud, and analytics workstreams matter more than a proprietary asset portfolio.
Match planning depth to estate uncertainty
Select Cognizant when Skygrade can reduce uncertainty through automated discovery, dependency mapping, and migration wave planning. Select Accenture when myNav-based workload analysis must produce target-cloud architecture recommendations before implementation.
Set the required governance boundary
Select Tata Consultancy Services when MasterCraft DataPlus must automate profiling, lineage capture, privacy checks, and validation across heterogeneous sources. Select IBM when Cloud Pak for Data and DataStage must combine policy controls with reusable transformation jobs, while accepting a more complex product landscape.
Test the operating model across regions
Infosys and Wipro suit multinational programs that need broad cloud engineering and managed operations. Buyers should assign decision rights before mobilization because Infosys can introduce multiple management layers and Wipro engagement quality can vary across regional teams.
Prioritize domain process ownership
Select Genpact when finance, supply chain, or customer operations should define modernization priorities and controls. Select Deloitte when regulated industry reference architectures and alliance coverage across major cloud and analytics platforms carry greater weight.
Organizations That Benefit From Structured Modernization Delivery
The strongest fit occurs where legacy estates span several platforms, business units, or regulatory boundaries. These programs need more than isolated migration labor because architecture decisions, validation, operating models, and post-cutover ownership must align.
Multinational enterprises with fragmented legacy estates
Tata Consultancy Services, Infosys, Cognizant, and Wipro provide delivery structures for multi-country programs spanning legacy systems, cloud environments, and several business units.
Regulated organizations with sensitive records
Hexaware supports governance and migration execution for regulated enterprises, while IBM combines policy controls with catalog, lineage, and quality functions through Cloud Pak for Data.
Enterprises with SAP, mainframe, and analytics dependencies
Capgemini coordinates these workstreams through migration factories, and Deloitte supplies industry-specific reference architectures for complex regulated environments.
Operations-led organizations linking technology changes to business processes
Genpact connects data engineering with finance, supply chain, and customer operations. Its domain-led model suits programs where process documentation and operational controls shape the modernization scope.
Common Errors in Data Modernization Procurement
Large providers offer different combinations of proprietary tooling, cloud engineering, industry assets, and managed services. A shortlist can misrepresent those differences if it treats every provider as interchangeable or ignores the internal governance burden.
Selecting a provider without testing its proprietary tooling against the actual estate
Require Hexaware to map Amaze and RAPID workflows to the source platforms, target platforms, conversion tasks, and testing scope. Require Cognizant to demonstrate how Skygrade handles dependency mapping and migration wave planning for the identified estate.
Assuming a broad delivery framework creates a single control plane
Ask IBM to identify which Cloud Pak for Data controls and DataStage functions are included in the proposed architecture. Ask Infosys to document ownership across Cobalt, hyperscaler services, enterprise applications, and managed operations.
Underestimating governance and decision latency in large programs
Define architecture authority, escalation paths, regional responsibilities, and cutover approvals before selecting Tata Consultancy Services, Infosys, Deloitte, or Accenture. These providers can support large programs, but each may involve multiple teams and management layers.
Treating industry coverage as interchangeable across providers
Match Capgemini to SAP and mainframe coordination, Deloitte to regulated industry reference architectures, and Genpact to finance, supply chain, and customer operations. Require named specialists for the business domains that determine migration priorities.
Ignoring administration and API limitations in the operating model
Test Wipro's administration controls and API surface during solution design because its service model is less standardized than specialist platforms. Test Genpact's provisioning controls and public API documentation before assigning internal teams to ongoing platform administration.
How We Selected and Ranked These Providers
We evaluated Hexaware, Tata Consultancy Services, Cognizant, Infosys, Accenture, Deloitte, Capgemini, IBM, Wipro, and Genpact across migration execution, cloud architecture, automation, governance, industry coverage, and managed operations. Features accounted for 40% of the ranking, while ease of use and value accounted for 30% each.
Hexaware led because Amaze, RAPID, Tensai, and RapidX combine assessment, platform modernization, testing, engineering, and operations assets with broad enterprise delivery capacity. We also weighed Hexaware's ability to support regulated legacy database, warehouse, lake, and reporting migrations across cloud platforms.
Frequently Asked Questions About Data Modernization
Which data modernization service fits a multinational enterprise with several legacy estates?
How do providers reduce risk during legacy data migration?
When is a managed modernization service preferable to a self-directed platform?
What technical requirements should be defined before a modernization engagement begins?
How do data modernization services address security and compliance?
What breaks if a modernization program treats data engineering as an isolated technology project?
Which provider suits an enterprise with SAP, mainframe, cloud, and analytics workloads?
What should an enterprise expect during onboarding and initial discovery?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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