Enterprise Data & Cloud Consulting

We architect the data platforms your enterprise runs on.

iShan Consulting LLC designs, modernizes, and validates large-scale data systems across Azure and AWS — turning fragile legacy pipelines into resilient, cloud-native infrastructure.

100%
data integrity validated
Azure + AWS
multi-cloud expertise
End‑to‑end
discovery to delivery
Platforms & tooling Azure Data Factory Synapse Analytics AWS Glue Databricks Oracle IBM DataStage
What we do

Specialized services, delivered with engineering rigor.

Every engagement is scoped, documented, and validated — so the systems we build hold up long after handoff.

Microsoft Azure

Azure Data Architecture

End-to-end environment provisioning, pipeline design, and schema mapping within Azure Data Factory, Synapse Analytics, and enterprise cloud data lakes.

  • ADF pipeline & dataflow design
  • Synapse & data lake architecture
  • Schema mapping & orchestration
Amazon Web Services

AWS Cloud Integration

Refactoring legacy computing tasks into native AWS data flows, optimizing cluster runtimes, and securing elastic storage tier configurations.

  • Native AWS data flow migration
  • Cluster runtime optimization
  • Elastic storage security
Performance Tuning

Legacy ETL Modernization

Systematic code refactoring to diagnose execution bottlenecks, resolve severe memory limitations, and ensure 100% data integrity validation across target systems.

  • Bottleneck diagnosis & tuning
  • Memory & runtime optimization
  • Full data integrity validation
How we work

A disciplined, iterative methodology.

We don't improvise on production data. Each project follows a repeatable framework refined across complex enterprise migrations.

01

Discovery

We map every job, dependency, and data flow before touching a line of code — so nothing breaks in silence.

02

Design

Target architecture, schema mapping, and orchestration are documented and reviewed against your standards.

03

Build

Pipelines are built incrementally in tested, reviewable increments — never a risky big-bang cutover.

04

Validate

Row-level reconciliation and integrity checks confirm the new system matches the old, exactly.

Capabilities

Deep expertise across the modern data stack.

Azure Data Factory
Synapse Analytics
AWS Glue & EMR
Databricks & Spark
Oracle & SQL Server
IBM DataStage
Data Lake & Lakehouse
ETL / ELT Pipelines
Schema & Data Modeling
CI/CD for Data
# migrate legacy pipeline → cloud-native
pipeline "customer_ingest" {
  source = oracle.prod.customers
  stage  = adls."parquet"
  transform = dataflow.normalize()
  load  = synapse.dim_customer
  validate = reconcile(rows, checksum)
}
# ✓ 100% row match — 0 discrepancies
Why iShan

The difference is in the details we refuse to skip.

Integrity, proven

We don't claim a migration is done until row counts, checksums, and business logic reconcile against the source. Trust is earned in the validation step.

Senior, hands-on

You work directly with an engineer who has lived in production data systems — not a layer of account managers between you and the work.

Documented, always

Every engagement leaves behind clear documentation — architecture, decisions, and runbooks your team can own long after we're gone.

Outcomes

Results that hold up in production.

Representative outcomes from data modernization engagements.

100%

Data integrity preserved

Row-level reconciliation across migrated tables — zero discrepancies between legacy and modern targets.

Validated platform migration outcome.

60%+

Faster pipeline runtimes

Bottleneck diagnosis and refactoring cut execution times and memory pressure on critical jobs.

Validated platform migration outcome.

Weeks

Not months to migrate

A structured, automated methodology compresses delivery timelines without cutting corners.

Validated platform migration outcome.

Client voice

Proven credibility from large-scale modernizations.

"iShan's lead architect brought multi-terabyte data warehouse experience to our core transformation projects, consistently identifying hidden schema anomalies and ensuring flawless quality across systems processing billions of operational records."
IT Executive Major Entertainment & Media Syndicate
"iShan's core architectural frameworks proved crucial for our legacy platform migrations. Complex data pipeline modernization initiatives were completed strictly on time with minimal rework and absolute structural alignment."
Operations Administrator Public Sector Enterprise Infrastructure
FAQ

Common questions.

Enterprise data and cloud work — Azure and AWS platform architecture, legacy ETL modernization, pipeline performance tuning, and data migration projects where integrity matters.

Yes. We frequently augment internal teams, leaving behind documentation and runbooks so your engineers can own and extend the systems we build.

Validation is a first-class phase, not an afterthought. We reconcile row counts, checksums, and business logic against the source system before any project is considered complete.

With a short consultation to understand your systems and goals, followed by a discovery phase that maps your current state before any build work begins.

Get in touch

Let's talk about your data.

Tell us what you're working on and what's getting in the way. Reach our technical architecture office directly, or use the secure form.

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