DATA PLATFORM MODERNIZATION
Modernize your data platform without rebuilding the migration by hand.
Datachecks combines specialized AI agents with migration experts to understand legacy data estates, generate mappings, translate migration logic, and continuously validate the move to modern platforms such as Snowflake, Databricks, BigQuery, and Microsoft Fabric.
LEGACY DATA ESTATE
Schemas
Tables
Views
SQL
Stored procedures
ETL logic
Jobs
Dependencies
DATACHECKS
CONTROLLED EXECUTION
UNDERSTAND
MAP
TRANSLATE
VALIDATE
MODERN DATA PLATFORM
Snowflake
Databricks
BigQuery
Microsoft Fabric
THE MODERNIZATION CHALLENGE
Moving the data is rarely the hardest part.
Enterprise data platforms accumulate years of schemas, SQL, stored procedures, transformations, dependencies, jobs, and business rules. Moving to a modern platform means understanding and rebuilding that logic — while proving the migrated data still behaves correctly.
01
Legacy complexity
Thousands of objects distributed across databases, warehouses, scripts, and transformation tools.
02
Hidden dependencies
Tables, views, procedures, jobs, and downstream workloads depend on one another in ways that are difficult to document manually.
03
Manual mapping
Source-to-target mappings are often maintained in spreadsheets and require repeated engineering review.
04
Logic conversion
SQL dialects, stored procedures, transformations, and platform-specific behavior must be translated to the target environment.
05
Validation burden
Teams must prove that structure, logic, data, and business outcomes remain correct after migration.
A modernization program is not just a data copy. It is a reconstruction of the data estate.
MIGRATION SCOPE
Modernization goes far beyond tables.
Datachecks helps teams reason across the different artifacts that make up an enterprise data estate.
The migration succeeds only when the data, logic, context, and evidence move together.
THE MIGRATION LIFECYCLE
Understand. Map. Translate. Validate.
Datachecks turns the major phases of data platform modernization into controlled agent workflows, with migration experts handling decisions, exceptions, and sign-off.
01 · UNDERSTAND
Build an executable understanding of the legacy estate.
AGENTS · Assessment + Discovery
Object inventory · Schemas · Dependencies · Data patterns · Migration complexity · Risk and scope
OUTCOME · Reduce weeks of manual assessment and discovery work.
ESTATE ASSESSMENT
ILLUSTRATIVE
OBJECTS
10,428
DEPENDENCIES
1,217
SCHEMAS
184
HIGH-COMPLEXITY AREAS
IDENTIFIED
SOURCE-TO-TARGET MAPPING
ILLUSTRATIVE
customer_id VARCHAR(20)
customer_key STRING
TRANSFORM
TRIM → UPPERCASE
CONFIDENCE
97%
status_code → customer_status
72% · REVIEW
02 · MAP
Generate source-to-target mappings instead of managing them entirely by spreadsheet.
AGENTS · Mapping Agent
Mappings generated from source and target metadata and migration context, then reviewed where required.
OUTCOME · Shift repetitive mapping work to automation while keeping ambiguous decisions visible.
03 · TRANSLATE
Convert legacy logic without rewriting everything manually.
AGENTS · Translation Agent
SQL dialects · Stored procedures · Functions · Transformation logic · Platform-specific syntax
OUTCOME · Compress one of the most engineering-intensive phases of modernization.
TRANSLATION OUTPUT
ILLUSTRATIVE
SOURCE
Oracle PL/SQL
TARGET
Snowflake SQL / Databricks SQL
TRANSLATED
12 objects
REQUIRE REVIEW
2
SYNTAX
VALIDATED
VALIDATION & RECONCILIATION
ILLUSTRATIVE
TESTS
8,421
PASSED
8,397
EXCEPTIONS
24
SOURCE ROWS
12,419,812
TARGET ROWS
12,419,812
MATCHED
100%
04 · VALIDATE
Prove that the migrated platform is right before cutover.
AGENTS · Validation + Reconciliation
Structural checks · Data comparison · Row counts · Aggregates · Business-rule tests · Reconciliation · Discrepancy drill-down
OUTCOME · Move faster without sacrificing confidence in the migrated data.
AI-NATIVE EXECUTION
Automate the repetitive migration work. Keep experts on the decisions.
Six specialized agents work across different migration decisions rather than relying on one generic AI assistant.
Understands migration scope, complexity, and risk.
Profiles the legacy estate, relationships, metadata, and dependencies.
Generates source-to-target mappings and surfaces ambiguity for review.
Converts legacy SQL, procedures, and transformation logic to target-native implementations.
Generates and executes migration tests across structure, logic, and data.
Compares source and target outcomes and helps isolate discrepancies.
AI executes the repeatable work. Migration experts own the critical decisions.
COMMON MODERNIZATION PROGRAMS
Built for the platforms enterprises are moving toward.
Datachecks can be applied across common data platform modernization paths. Automation depth depends on source, target, and migration scope.
Snowflake
Oracle → Snowflake
Teradata → Snowflake
SQL Server → Snowflake
DB2 → Snowflake
Redshift → Snowflake
Explore Snowflake Migrations
Databricks
Oracle → Databricks
Teradata → Databricks
Redshift → Databricks
SQL Server → Databricks
Legacy warehouse → Databricks
Explore Databricks Migrations
BigQuery
Oracle → BigQuery
Teradata → BigQuery
SQL Server → BigQuery
Legacy analytical platform → BigQuery
Explore BigQuery Migrations
Microsoft Fabric
SQL Server → Fabric
Oracle → Fabric
Microsoft data-estate modernization → Fabric
Explore Fabric Migrations
Explore All Migration Paths
HOW WE DELIVER
One migration engine. Two delivery models.
Datachecks can deliver the modernization directly, or power the delivery model of the system integrator already running the program.
DATACHECKS-LED
Datachecks delivers the modernization.
Our migration experts use Datachecks agents to execute the work across discovery, mapping, translation, validation, reconciliation, and cutover readiness.
One accountable migration team
Lower manual delivery effort
Continuous validation
Faster execution
SI-LED
Your system integrator delivers. Datachecks powers the execution.
System integrators can embed Datachecks into their delivery model to automate repeatable migration work and standardize execution across programs.
Improve delivery margins
Increase project throughput
Standardize execution
Reuse migration knowledge
Explore Migration Factory
PROVEN AT ENTERPRISE SCALE
Built for estates where scale and accuracy both matter.
An enterprise banking modernization delivered with Datachecks across a multi-technology legacy estate.
LEGACY ESTATE
Oracle
MySQL
Microsoft SQL Server
SAP ASE
SAP IQ
DATACHECKS · MAP · TRANSLATE · VALIDATE · RECONCILE
SAP IQ + DATABRICKS
10K+
TABLES IN THE LEGACY ESTATE
900 tables validated with a 2-person team
OPERATIONAL PROOF
SCOPE · MAPPING · TRANSLATION · VALIDATION · RECONCILIATION
ENTERPRISE DEPLOYMENT
The migration engine runs where the data lives.
Deploy Datachecks within enterprise-controlled infrastructure, connect approved AI models, and keep migration data, metadata, execution, and evidence under enterprise control.
Private deployment
BYOM
SAML SSO
SOC 2
ISO 27001
FREQUENTLY ASKED QUESTIONS
Questions about data platform modernization.
What parts of a data platform migration can Datachecks automate?
Is Datachecks only for moving data to Snowflake or Databricks?
Does Datachecks replace migration engineers?
Can Datachecks handle SQL and stored procedure conversion?
How does Datachecks validate a modernized data platform?
Can Datachecks work with our existing system integrator?
Bring us your hardest migration.
Datachecks combines specialized AI agents with migration experts to deliver complex migrations faster — with validation and reconciliation built in.