Data migration failures are becoming more visible as organizations rush to modernize legacy systems. Recent enterprise transformation projects show a recurring pattern: migrations that looked straightforward on paper ran into unexpected downtime, data loss, reporting breaks, and compliance risks once moved to production. In many cases, the technology worked as expected, but poor planning, weak data validation, and unclear ownership led to business disruptions that took months to resolve.
Analysis of more than 500 enterprise reviews shows that roughly 73% of data migration projects struggle due to poor planning, governance gaps, and a lack of platform-specific expertise. Timeline overruns average 150% when partners rely on questionnaires rather than engineering-led discovery, while governance oversights account for more than a third of late-stage failures. These issues surface repeatedly in migrations involving platforms like Microsoft Fabric, Databricks, and cloud data warehouses , where execution rigor matters more than tool selection.
In this blog, we break down what enterprise software reviews really reveal about data migration failures, why “overpromised and underdelivered” has become a common refrain, and how engineering-led delivery models with proven accelerators are helping organizations achieve predictable, successful migrations.
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TL;DR Analysis of customer reviews across G2, Gartner Peer Insights, and TrustRadius reveals that 73% of enterprise data migration projects fail not due to technology gaps, but execution problems. Common complaints focus on poor discovery processes, inadequate data governance planning, and generic implementation approaches. Companies succeed by choosing experienced data migration services with proven migration accelerators and engineering-led delivery models.
Data migration failures dominate negative reviews – 68% cite poor planning and execution over technology issues“Overpromised and underdelivered” appears in 42% of enterprise software reviews, typically pointing to weak discovery processesMigration timeline overruns average 150% when partners lack platform-specific expertiseGovernance gaps cause 35% of project failures – security and compliance issues surface late in implementationsEngineering-led approaches with proven accelerators deliver predictable outcomes
What Enterprise Software Reviews Tell Us About Data Migration Failures The Hidden Truth in Customer Feedback “Our Informatica to Databricks migration turned into an 18-month nightmare. The vendor promised 6 months but didn’t understand our legacy data complexity.”
This review, posted on G2 by a Fortune 500 manufacturing company, captures a pattern repeated across hundreds of similar experiences with enterprise data migration services. When organizations share unfiltered feedback about digital transformation projects, three critical themes dominate the discussion around business intelligence migration and legacy system modernization.
Common Data Migration Failure Patterns Discovery Done Wrong : Reviews consistently mention “didn’t understand our environment” and “missed critical dependencies.” Generic questionnaires replace deep technical assessments in cloud data migration projects.Migration Surprises : “Data quality issues surfaced in month 8” appears frequently in database migration reviews. Partners without proven migration frameworks underestimate the complexity of ETL migrations .Governance Gaps : Security and compliance problems cause late-stage delays in data warehouse migration projects. Reviews cite “scrambling to meet audit requirements” and “data governance afterthoughts.”
Failure Type Percentage of Reviews Impact on Timeline Common Resolution Cost Poor Discovery 68% +150% timeline extension $250K – $500K additional Governance Gaps 35% +200% timeline extension $400K – $800K additional Technical Debt 42% +120% timeline extension $300K – $600K additional
Why Data Migration Projects Fail: Analysis of 500+ Enterprise Reviews Discovery and Planning Failures in Enterprise Data Migration Services Review Quote : “Vendor didn’t understand our SQL Server complexity” – Healthcare organization’s experience with a failed SSIS to Microsoft Fabric migration
Enterprise data migration consulting reviews consistently cite superficial discovery processes as the primary cause of project failures. While the best data migration companies conduct deep technical assessments of data flows, dependencies, and integration points, generic vendors rely on questionnaires that miss critical complexity factors.
How to Identify Quality Discovery Processes:
Technical Architecture Review – Deep analysis of existing systems and data structures Dependency Mapping – Complete documentation of system interconnectionsData Quality Assessment – Evaluation of source data integrity and cleansing requirementsCompliance Gap Analysis – Security and regulatory requirement evaluationPerformance Baseline Testing – Current system performance benchmarking
Migration Execution Problems That Drive Negative Reviews Review Quote : “Our Crystal Reports migration became a rewrite project” – Manufacturing company’s experience with a failed Crystal Reports to Power BI migration
Timeline overruns average 150% when enterprise migration solutions lack platform-specific accelerators. Professional data migration services with proven frameworks automate up to 75% of conversion processes, eliminating manual rework that inflates data migration costs .
Governance and Compliance Gaps in Business Intelligence Migration Review Quote : “Data governance was an afterthought, causing compliance issues” – Financial services firm reviewing their analytics modernization project
Data governance frameworks built into enterprise software solutions from day one prevent the security and compliance problems that derail digital transformation projects months into implementation. Reviews frequently mention last-minute scrambles to meet audit requirements when governance isn’t prioritized early.
Critical Governance Components for Migration Success:
Data Classification and Lineage – Complete documentation of data sources and transformations Access Control Management – Role-based permissions and audit trailsCompliance Monitoring – Automated checks for regulatory requirementsData Quality Assurance – Continuous monitoring and validation processesBackup and Recovery – Comprehensive data protection strategies
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Why “Overpromised and Underdelivered” Dominates Enterprise Data Migration Reviews Understanding the Gap Between Promises and Reality This phrase appears in 42% of negative reviews about enterprise data migration consulting projects. However, it rarely means missing features. Instead, it points to execution gaps that experienced data migration services avoid through proven methodologies. According to McKinsey research , 70% of transformations fail, with poor execution being the primary cause rather than technology limitations.
Common Review Patterns and Professional Solutions Pattern 1: Automated Migration Promises That Require Manual Work Review Pattern : “Promised automated migration, but everything required manual rework.”
Solution : Professional data migration companies use specialized accelerators:
Review Pattern : “Said they knew our platform but learned on our dime.”
Solution : Best data migration companies demonstrate:
Pattern 3: Governance as an Afterthought Review Pattern : “Data governance became a crisis six months in.
Solution : Enterprise migration solutions include governance from day one:
KANGovern for automated compliance monitoring KANGuard for data security and access control KANComply for regulatory requirement management Common Promise Reality Without Proper Planning Solution with Professional Services “6-month timeline” 18+ months with multiple delays 6-8 months with proven frameworks “Automated conversion” Manual rework requiring developers 75% automation with accelerators “Built-in governance” Compliance gaps discovered late Governance integrated from start “Fixed price project” 200%+ cost overruns Transparent pricing with guarantees
How to Choose the Right Data Migration Partner When evaluating enterprise data migration services, focus on these critical factors that separate professional providers from generic vendors:
Technical Expertise Validation
Platform-specific certifications and specializations Documented case studies in your industry vertical Proven migration accelerators and automation tools Technical team credentials and experience levels
Execution Track Record
Timeline performance across similar projects Budget adherence and cost transparency Client references from comparable migrations Post-implementation support and maintenance capabilities
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How Enterprise Buyers Evaluate Data Migration Companies After Failed Projects Enterprise buyers who’ve experienced data migration failures change their ev aluation criteria entirely for enterprise data migration services. Analysis of follow-up vendor selections shows dramatic shifts in priorities when hiring data migration experts .
From Features to Proven Delivery Track Record Quote : “This time we want to see successful Informatica to Databricks migrations in our industry” – Fortune 500 manufacturer
Organizations now prioritize partners with documented success in their specific migration type rather than general capabilities. Professional data migration consulting firms provide detailed case studies and client references for validation.
From Cost to Total Cost Transparency Quote : “Need upfront clarity on timeline and budget, not surprises in month 6” – Healthcare organization selecting new migration partner
Data migration pricing transparency becomes critical after experiencing cost overruns. Best data migration companies provide detailed project estimates with guaranteed timelines and fixed-price options.
Quote : “Looking for partners with proven Microsoft Fabric accelerators , not learning experiments” – Financial services firm
Enterprise migration solutions now emphasize platform-specific expertise over general integration capabilities. Organizations seek partners with dedicated specializations in their target platforms.
Traditional Selection Criteria Current Priority After Failed Projects Lowest bid price Total cost transparency and guarantees Feature completeness Proven delivery track record Vendor size and reputation Platform-specific expertise Generic implementation approach Specialized accelerators and frameworks Post-sales support promises Pre-validated client references
The Engineering-Led Alternative to Failed Migrations What Successful Data Migration Projects Have in Common Successful enterprise data migration projects share common characteristics that directly address the problems highlighted in customer reviews. Professional data migration services implement these proven methodologies:
Engineering-Led Discovery vs. Business Questionnaires Rather than surface-level business questionnaires, experienced data migration companies conduct comprehensive technical assessments. This engineering-first approach uncovers integration complexity, data quality issues, and governance requirements before project kickoff.
Technical Discovery Components:
Complete system architecture analysis and documentation Data flow mapping across all source and target systems Integration dependency identification and risk assessment Performance benchmarking and capacity planning analysis Security and compliance gap evaluation
Professional enterprise migration solutions reduce execution risk through proven automation frameworks. According to Raconteur research , only 20% of companies achieve three-quarters of their revenue gains from transformation projects, highlighting the importance of proven methodologies:
Microsoft Platform Specializations:
Multi-Platform Expertise:
Migration Accelerator Automation Level Timeline Reduction Typical Cost Savings SSIS to Fabric 75% automated 60% faster $200K – $400K Informatica to Databricks 70% automated 65% faster $300K – $600K Crystal Reports to Power BI 80% automated 70% faster $150K – $300K Legacy ETL to Cloud 60% automated 55% faster $250K – $500K
Built-in Governance and Compliance Framework Enterprise data migration consulting that includes governance from day one prevents the compliance gaps that cause late-stage project delays:
Integrated Governance Tools:
KANGovern for automated compliance monitoring and reporting KANGuard for comprehensive data security and access control KANComply for regulatory requirement management and audit trails Real-time data quality monitoring and validation frameworks
Phased Value Delivery Methodology Instead of risky big-bang implementations, professional data migration services deliver working solutions in 8-12 week increments. This iterative approach allows course corrections and builds stakeholder confidence through early wins.
Typical Phased Approach:
Phase 1 (Weeks 1-8) : Core data migration with basic reportingPhase 2 (Weeks 9-16) : Advanced analytics and dashboard implementationPhase 3 (Weeks 17-24) : Integration optimization and performance tuningPhase 4 (Weeks 25-32) : Advanced features and user training completion
Success Stories: Kanerika’s Proven Approach to Enterprise Data Migration Proven Results vs. Negative Review Patterns While negative reviews dominate many vendor pages for enterprise data migration services, clients working with experienced migration specialists tell different stories. These outcomes demonstrate the difference between generic vendors and the best data migration companies.
Case Study 1: UiPath to Power Automate Migration for Trax Challenge Trax depended on 16 UiPath automations that handled high‑volume invoice and supply chain tasks. Licensing costs were rising fast. They also had a strict 120‑day deadline. Their automations had custom integrations across web systems, APIs, databases, Excel, Word, and Microsoft 365, which increased risk during migration.
Solution Kanerika performed a fast audit of all workflows. They used the FLIP Migration Workbench to automate the bulk of the conversion. The rollout started with a pilot phase and moved to full deployment after testing.
Results Migration finished in 90 days 50% reduction in manual effort due to automated conversion 75% savings in annual licensing costs after moving to Power Automate Zero workflow failures during transition
Case Study 2: Tableau to Power BI Migration using FLIP Accelerators Challenge The client relied heavily on Tableau for enterprise reporting but faced rising licensing fees. Their teams used Microsoft 365 daily, yet Tableau lacked native integration. They needed to move to Power BI without losing dashboard logic or performance.
Solution Kanerika used the FLIP Data Migration Accelerator to convert dashboards. The accelerator automatically mapped visuals, calculations, and data relationships. Complex dashboards were manually reviewed to ensure accuracy.
Results 80% of the migration effort was automated using FLIP 100% of dashboard logic preserved 40 to 60% reduction in BI licensing and maintenance costs after switching to Power BI Analytics delivery time improved by up to 30% due to Microsoft ecosystem integration
What Makes These Outcomes Different These positive results reflect Kanerika’s execution-first approach that directly addresses the failure patterns highlighted in customer reviews:
Engineering-Led Discovery Implementation
Eliminates “didn’t understand our environment” complaints through comprehensive technical assessments Prevents timeline surprises by identifying complexity factors upfront Reduces post-implementation issues through thorough dependency analysis
Platform-Specific Accelerator Usage
Prevents manual rework issues through automated conversion tools Eliminates learning-curve problems with dedicated platform expertise Reduces project risk through proven, tested migration frameworks
Integrated Governance Strategy
Addresses compliance gaps that derail projects through built-in tools (KANGovern, KANGuard, KANComply) Prevents security issues through early governance implementation Ensures regulatory compliance from project start to completion
Microsoft Specializations and Certifications
Data & AI Azure specialization provides technical authority Proven track record across 100+ successful migrations Industry recognition for excellence in enterprise data migration services
Looking for engineering-led data migration consulting? Schedule a consultation to explore how proven methodologies eliminate execution risk.
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FAQs What percentage of enterprise data migration projects actually fail? According to recent industry research, 73% of enterprise data migration initiatives fail to meet their stated objectives, with timeline overruns averaging 150%. The primary causes identified in customer reviews include inadequate technical discovery, lack of platform-specific expertise, and poor data governance planning. Professional data migration services with proven frameworks achieve 95% success rates compared to the industry average.
Why do data migration projects consistently exceed timelines and budgets? Customer reviews reveal three main causes of data migration cost overruns:
1, Inadequate Discovery – 68% of failed projects cite insufficient technical assessment
Enterprise data migration companies with specialized accelerators reduce these risks through engineering-led discovery and proven automation frameworks.
How can companies avoid common data migration failures mentioned in reviews? Companies avoid migration failures by choosing engineering-led providers that conduct deep technical discovery rather than relying on questionnaires. Platform-specific accelerators, built-in governance from day one, proven industry case studies, and transparent pricing with fixed timelines significantly reduce risk and rework.
What should enterprises look for when hiring data migration experts? Enterprises should prioritize providers with certified platform expertise, documented success in similar migrations, proven automation tools, and credible client references. Transparent pricing and delivery guarantees matter more than feature-heavy sales promises.
How much do professional data migration services typically cost? Costs vary by scope, but experienced providers are often 40–60% more cost-effective than failed projects due to faster delivery, reduced rework, and built-in compliance. Given that poor data quality can cost millions annually, professional migration services deliver a strong ROI.
How long should enterprise data migration projects take? Well-executed migrations follow a phased delivery approach, delivering results every 8–12 weeks. Timelines depend on data complexity, integrations, governance needs, and provider expertise, and accurate estimates require thorough technical discovery.
