Kanerika provides data migration services for Charlotte enterprises looking to modernize legacy data platforms without disrupting business operations. Our FLIP accelerators automate ETL conversion, BI report migration, and RPA rebuilds, helping reduce manual effort, licensing costs, and cutover risk.
Faster Migrations
Cost Savings
Predictable Timelines
FLIP, Kanerika’s IP-led accelerator, automates up to 80% of a data platform migration. Enter your asset counts to see the budget, engineering hours, and delivery weeks that automation takes out.
Charlotte enterprises often need reliable data migration services to modernize complex data environments across legacy platforms, cloud systems, analytics platforms, and business applications. Kanerika helps organizations modernize these environments through structured, automated data migration.
Move Informatica, Alteryx, or ADF workloads to Talend, Databricks, or Microsoft Fabric. FLIP pulls mappings and workflows straight from the repository rather than inferring them from documentation.
Convert Tableau, SSRS, Crystal Reports, or Cognos estates to Power BI. Calculated fields, filters, and row-level security definitions transfer as written instead of being reconstructed from old report output.
Rebuild UiPath estates on Microsoft Power Automate. Attended bots, scheduled processes, and XAML sequences carry exception handling forward, even where nobody documented the original logic.
FLIP is Kanerika's Intelligent Workflow Automation Platform. Each accelerator handles one source-to-target route, covering repository extraction, dependency mapping, conversion, and validation for that pairing specifically rather than a script reused across platforms.
Migration value shows up as reduced platform spend, shorter reporting cycles, less maintenance effort, and analytics that reflect current data rather than yesterday’s.
Migration
Migration
Migration
FLIP deploys into your own infrastructure through Docker and operates on metadata alone. Conversion runs where your systems already sit, which keeps regulated records inside the controls that govern them and shortens the third-party security review that normally delays migration kickoff.
We read table definitions, mappings, and dependency structures. Production records are never accessed, staged, or transmitted.
Execution stays inside your network perimeter, so there is no external transfer and no third-party access to govern.
Conversion logs, reconciliation output, and access records land in your environment under your own retention policy.
IMPACT covers the full arc from source inventory through post-cutover monitoring. Its value is in the gates, since most migration overruns trace back to a phase that was declared finished early.
Our approach is built to take uncertainty out of migration. Clear stages, a defined outcome at each one, and a team that stays with the program from first assessment through to steady state.
Understand Business Goals
Analyze Data & Workflows
Design Sound Solutions
Develop & Deploy Solutions
Ongoing Support
01
Understand Business Goals
02
Analyze Data & Workflows
03
Design Sound
Solutions
04
Develop & Deploy Solutions
05
Ongoing
Support
As a data migration company serving Charlotte, Kanerika works across the full source and target stack, from legacy on-premises platforms through to Microsoft Fabric, Databricks, Power BI, and Talend.
Kanerika provides data platform migration services for Charlotte enterprises across key industries, helping organizations modernize legacy data environments with minimal disruption.
FLIP automates most of the conversion work on a migration, pulling business logic straight from the source repository and validating each object as it converts. Cost tracks complexity rather than asset volume.
BI, ETL, RPA, and data platform migration handled by one accelerator, not four vendors.
Complexity, effort, risk, timeline, and cost mapped before you commit to the migration.
Parallel testing, row-count reconciliation, and checksums produce a documented parity report every time.
The pivotal partnerships with technology leaders that amplify our capabilities, ensuring you benefit from the most advanced and reliable solutions.
Data migration moves data and the logic that shapes it from one system to another. In an enterprise context that usually means retiring a legacy platform and standing up its replacement, carrying across the pipelines, reports, or automations that ran on it. The data itself is rarely the hard part. The accumulated business logic is.
Six stages. Inventory the source environment and its dependencies. Design the target architecture. Sequence the estate into waves. Convert assets onto the new platform. Reconcile output against the source. Then cut over and decommission. Programs that compress the first two stages generally pay for it during the fourth and fifth.
By running both platforms in parallel until the new one is proven. Consumers stay pointed at the legacy warehouse while the target is loaded and reconciled behind it. Only when output matches across a full reporting cycle do you redirect traffic. Rollback stays available throughout, which is what makes the cutover a decision rather than a gamble.
It is the replacement of an existing warehouse platform, including its schemas, load pipelines, and downstream reporting dependencies. Moving tables is straightforward. Reproducing the transformation logic, incremental load patterns, and historical corrections applied over years is what determines whether the new warehouse returns the same numbers as the old one.
Assess which workloads benefit from cloud compute and which are moving only because the contract ended. Design the target around those workloads. Convert pipelines and reports to platform-native equivalents rather than lifting them unchanged, since a lifted legacy pipeline usually costs more to run in the cloud than it did on premises. Validate, then cut over in waves.
Keep the conversion inside your own environment and restrict tooling to metadata wherever possible. Personal data should not enter a vendor platform during migration. Field-level mapping needs review before execution, because CRM schemas accumulate custom fields with inconsistent use. Reconcile record counts and key relationships before the legacy instance is switched off.
Sequence matters more than tooling. Consolidation fails when systems are merged before anyone agrees which one holds the authoritative version of a shared entity. Resolve that first, then migrate in waves with reconciliation between each. Kanerika handles this in the Map phase, before any conversion work is scheduled.
Reconcile at three levels. Record counts confirm nothing was dropped. Control totals confirm balances and aggregates match the source. Then a sample of period-end reports is regenerated on both platforms and compared line by line. For finance teams, matching totals with mismatched detail is the failure mode worth testing for specifically.
Ask what percentage of conversion is automated on your exact source and target, not in general. Ask what happens to logic that was never documented. Ask whether validation runs during conversion or at user acceptance testing. And ask for a converted-asset log from a comparable engagement. Vendors pricing by asset count are describing manual work.
Ask what percentage of conversion is automated on your exact source and target, not in general. Ask what happens to logic that was never documented. Ask whether validation runs during conversion or at user acceptance testing. And ask for a converted-asset log from a comparable engagement. Vendors pricing by asset count are describing manual work.
Data migration services help Charlotte businesses move data from legacy systems, databases, and applications to modern cloud, analytics, and enterprise platforms with minimal disruption.
Kanerika helps Charlotte enterprises plan, automate, execute, and validate complex data migrations using its FLIP accelerators, migration methodology, and platform expertise.
Yes. Kanerika supports cloud data migration and modernization across enterprise data environments, helping organizations transition from legacy platforms to modern cloud technologies.
Kanerika uses migration automation, structured methodologies, validation, and testing to reduce manual effort, downtime, errors, and cutover risk.
Kanerika supports migrations across databases, ETL platforms, BI platforms, legacy systems, cloud environments, and enterprise data platforms, depending on the migration requirements.
Limited seats available! Register Now
