Data Science

Big Data Migration & Modernization

Transform Legacy Systems to Modern Platforms

Migrate from on-premises Hadoop clusters to cloud-native platforms, modernize legacy data warehouses, and upgrade to current technologies-all with zero downtime and complete data integrity.

40+
Migrations Completed
400TB+
Data Migrated
100%
Zero Downtime
45%
Cost Reduction
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What is Big Data Migration & Modernization?

Transform legacy infrastructure

Big data migration moves data, workloads, and applications from legacy systems to modern platforms. Modernization goes further-re-architecting solutions to take advantage of cloud-native capabilities, managed services, and modern frameworks.

Common migration scenarios include: moving from on-premises Hadoop clusters to cloud data lakes, upgrading from legacy data warehouses to platforms like Snowflake or Databricks, migrating between cloud providers, and consolidating disparate data systems into unified platforms.

The business drivers are compelling: cloud platforms typically reduce total cost of ownership by 40-60% while improving performance and scalability. Managed services reduce operational burden. Modern tools improve developer productivity. The challenge is executing migration without disrupting ongoing operations.

Key Metrics

100%
Data Integrity
Complete validation
0 hours
Unplanned Downtime
Zero-downtime approach
40-60%
Cost Reduction
Post-migration savings
2-5x faster
Performance
Modern platforms

Why Choose DevSimplex for Big Data Migration?

Proven migration expertise

We have completed over 40 big data migrations, moving more than 400TB of data to modern platforms. Every migration achieved zero unplanned downtime. Our clients have realized average cost reductions of 45% post-migration.

Big data migrations are complex. They involve moving massive data volumes while maintaining ongoing operations. Workloads must be translated to new technologies. Users need to be retrained. Our structured methodology addresses each challenge systematically.

We understand both source and target technologies deeply. Whether you are migrating from on-premises Hadoop, legacy Teradata, or an older cloud platform, we know the source system intricacies. We are experts in target platforms including AWS, Azure, GCP, Databricks, and Snowflake.

Requirements

What you need to get started

Current State Documentation

required

Inventory of existing systems, data volumes, and workloads.

Business Continuity Requirements

required

Acceptable downtime windows and data freshness requirements.

Target Platform Selection

required

Decision on target cloud/platform or requirements for selection.

Stakeholder Alignment

required

Executive sponsorship and stakeholder agreement on migration approach.

Team Availability

recommended

Internal resources for testing, validation, and knowledge transfer.

Common Challenges We Solve

Problems we help you avoid

Data Integrity

Impact: Data loss or corruption during migration undermines trust.
Our Solution: Comprehensive validation frameworks compare source and target at every stage with automated reconciliation.

Business Continuity

Impact: Migration downtime disrupts operations and revenue.
Our Solution: Zero-downtime migration strategies with parallel running and phased cutovers.

Workload Compatibility

Impact: Jobs that worked on legacy may fail on new platforms.
Our Solution: Systematic workload analysis, translation, and testing before cutover.

Timeline and Budget

Impact: Migrations often overrun estimates.
Our Solution: Proven methodology with phase gates, risk management, and contingency planning.

Your Dedicated Team

Who you'll be working with

Migration Lead

Manages overall migration program and stakeholder communication.

12+ years, 20+ migrations

Data Engineer

Executes data migration and validates integrity.

8+ years in big data

Platform Engineer

Builds and configures target platform infrastructure.

5+ years in cloud platforms

How We Work Together

Migration programs typically span 12-24 weeks with dedicated team throughout.

Technology Stack

Modern tools and frameworks we use

AWS EMR/Glue

AWS big data services

Azure Synapse

Azure analytics

Databricks

Unified analytics platform

Snowflake

Cloud data warehouse

Migration Tools

Data transfer utilities

Migration & Modernization ROI

Modern platforms deliver immediate and ongoing value.

40-60% reduction
Infrastructure Costs
Year 1
50% reduction
Operational Costs
Year 1
2-5x improvement
Query Performance
Immediate

Why We're Different

How we compare to alternatives

AspectOur ApproachTypical AlternativeYour Advantage
ApproachZero-downtime methodologyPlanned outage windowsNo business disruption
ValidationAutomated data validationManual sampling100% data integrity
OptimizationWorkload optimization includedLift-and-shift onlyBetter performance and costs

Key Benefits

Significant Cost Reduction

Cloud platforms and managed services typically reduce TCO by 40-60% compared to on-premises systems.

40-60% savings

Improved Performance

Modern platforms deliver 2-5x faster query performance with better scalability.

2-5x faster

Zero Downtime

Our migration methodology ensures continuous operations throughout the transition.

0 downtime

Complete Data Integrity

Automated validation ensures 100% data accuracy from source to target.

100% validated

Cloud-Native Benefits

Leverage elastic scaling, managed services, and continuous innovation of cloud platforms.

Cloud-native

Reduced Operations

Managed services eliminate hardware management and reduce operational burden.

50% less ops

Our Process

A proven approach that delivers results consistently.

1

Assessment & Planning

2-4 weeks

Analyze current state, define target architecture, and create detailed migration roadmap.

Current state assessmentTarget architectureMigration roadmap
2

Target Platform Setup

2-4 weeks

Build and configure target platform infrastructure with security and networking.

Target infrastructureSecurity configurationConnectivity setup
3

Data Migration

4-8 weeks

Execute data migration with continuous validation and integrity checks.

Migrated dataValidation reportsSync mechanisms
4

Workload Migration

3-6 weeks

Migrate and optimize workloads including jobs, pipelines, and applications.

Migrated workloadsPerformance benchmarksOptimization report
5

Cutover & Decommission

1-2 weeks

Execute production cutover and decommission legacy systems.

Production cutoverDecommission planFinal documentation

Frequently Asked Questions

How long does a big data migration take?

Typical migrations take 12-24 weeks depending on data volume and complexity. Simple migrations may complete in 12 weeks, while large enterprise migrations with complex workloads often require 20-24 weeks.

Can we migrate with zero downtime?

Yes, our methodology is designed for zero-downtime migration. We use parallel running, incremental sync, and phased cutovers to maintain continuous operations. Users experience no disruption during the transition.

How do you ensure data integrity?

We implement automated validation frameworks that compare source and target data at every stage. Row counts, checksums, and business rule validations ensure 100% accuracy. Discrepancies are identified and resolved before cutover.

What happens to our existing reports and applications?

We migrate and adapt existing workloads to the new platform. Reports are recreated or connected to new data sources. Applications are updated to use new endpoints. We validate everything works before cutover.

How much can we expect to save?

Most clients see 40-60% reduction in total cost of ownership. Savings come from eliminating hardware costs, reduced operations overhead from managed services, and optimization of cloud resources. We provide detailed cost projections during planning.

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Let's discuss how we can help transform your business with big data migration & modernization services.

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