Blogs

Insights, updates, and best practices for data acceleration

Using Synthetic Data for Safe Migration Testing in HIPAA and PCI Environments data engineering blog cover

July 1, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

Using Synthetic Data for Safe Migration Testing in HIPAA and PCI Environments

Testing a migration properly means running realistic data through the new platform. In regulated environments, that creates a tension: the most realistic data is production data, and production data is exactly what you are not supposed to copy into a test environment. Using real records under HIPAA, PCI, or GDPR triggers obligations and risk that most teams would rather avoid. Synthetic data is how you resolve the tension without weakening the test.

How to Assess a Legacy Data Warehouse Before a Cloud Migration data engineering blog cover

June 30, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

How to Assess a Legacy Data Warehouse Before a Cloud Migration

The decision to move a legacy data warehouse to the cloud is usually the easy part. The hard part is knowing what you are actually moving. A migration that begins without a grounded assessment tends to discover its real scope during execution, which is the most expensive place to discover anything. A disciplined pre-migration assessment is what turns an open-ended program into a plan.

Converting SSIS and T-SQL to Microsoft Fabric: What Breaks and How to Plan for It data engineering blog cover

June 25, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

Converting SSIS and T-SQL to Microsoft Fabric: What Breaks and How to Plan for It

On paper, moving from SQL Server with SSIS to Microsoft Fabric looks like a translation exercise. In practice, two things make it harder than it appears: SSIS does not have a single clean equivalent in Fabric, and T-SQL on the target is close to but not the same as what your stored procedures assume. Planning for both before you start is what keeps the migration from stalling halfway through.

Synapse Dedicated SQL Pool to Microsoft Fabric: A Pre-Migration Assessment Checklist data engineering blog cover

June 25, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

Synapse Dedicated SQL Pool to Microsoft Fabric: A Pre-Migration Assessment Checklist

Microsoft has placed Azure Synapse Analytics into maintenance mode while Microsoft Fabric receives the platform's forward investment. For teams running a Synapse Dedicated SQL Pool, that turns migration from an open-ended option into a planning decision with a clock attached. The risk is not the destination. Fabric is a capable target. The risk is starting execution before the estate is properly understood.

Synapse Dedicated SQL Pool to Microsoft Fabric: A Practical Migration Guide data engineering blog cover

May 21, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

Synapse Dedicated SQL Pool to Microsoft Fabric: A Practical Migration Guide

Microsoft Fabric is now the strategic direction for new analytics capabilities. Teams running production workloads on Synapse Dedicated SQL Pool need a migration plan grounded in source-system facts, not object-count estimates. This guide explains the issues that derail Synapse to Fabric migrations and a practical five-phase approach.

SQL Server to Microsoft Fabric: T-SQL Compatibility Is Not the Whole Story data engineering blog cover

May 21, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

SQL Server to Microsoft Fabric: T-SQL Compatibility Is Not the Whole Story

SQL Server to Fabric looks straightforward because both platforms sit in the Microsoft ecosystem. In practice, T-SQL compatibility is only one part of the migration. SSIS packages, SQL Agent jobs, Windows Authentication, CLR objects, linked servers, and on-premises networking all need a separate plan.

Oracle to Microsoft Fabric: Why PL/SQL Conversion Drives the Timeline data engineering blog cover

May 21, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

Oracle to Microsoft Fabric: Why PL/SQL Conversion Drives the Timeline

Oracle to Microsoft Fabric is a rewriting effort, not a simple platform migration. PL/SQL and T-SQL follow different procedural models, and Oracle packages, cursor loops, triggers, sequences, and autonomous transactions require careful redesign. This guide explains why PL/SQL conversion drives the timeline.

Teradata to Microsoft Fabric: BTEQ Scripts and the Real Bottlenecks data engineering blog cover

May 15, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

Teradata to Microsoft Fabric: BTEQ Scripts and the Real Bottlenecks

Teradata to Fabric requires more than SQL translation. BTEQ scripts, FastLoad and MultiLoad jobs, QUALIFY clauses, Teradata-specific functions, and PE/AMP performance assumptions all need analysis or redesign. The biggest hidden risk is often tribal knowledge in undocumented scripts.

Microsoft Fabric Migration: A Platform-by-Platform Guide for Enterprise Teams data engineering blog cover

May 5, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

Microsoft Fabric Migration: A Platform-by-Platform Guide for Enterprise Teams

Microsoft Fabric migration is not one standard program. Synapse, SQL Server, Oracle, and Teradata each bring different language gaps, architecture gaps, risks, and timelines. This guide compares the four paths so enterprise teams can plan with realistic expectations.

AI-Augmented Legacy Code Modernization: A Four-Stage Framework data engineering blog cover

April 29, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

AI-Augmented Legacy Code Modernization: A Four-Stage Framework

Legacy code modernization usually stalls because inventory is incomplete, complexity scoring is skipped, conversion becomes sequential, and validation is left too late. This framework shows how AI acceleration can support the volume work while engineers retain responsibility for design and review.

The Three Categories of Data Engineering Work: A Framework for AI Augmentation data engineering blog cover

April 28, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

The Three Categories of Data Engineering Work: A Framework for AI Augmentation

Not every data engineering task should be automated. Some tasks require senior judgment, some are suitable for AI acceleration with engineer review, and some can be fully automated. This framework helps teams decide where AI fits task by task.

Why Most Data Modernization Programs Miss Their Deadlines data engineering blog cover

April 22, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

Why Most Data Modernization Programs Miss Their Deadlines

Most data modernization programs miss deadlines for structural reasons, not lack of effort. Estimates are often based on assumptions, discovery takes longer than planned, architecture decisions stall, and validation issues appear too late. This blog explains the common failure modes and practical fixes.

It Is Time to Rethink How We Do Data Engineering data engineering blog cover

March 10, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

It Is Time to Rethink How We Do Data Engineering

The traditional data engineering lifecycle was built around manual analysis, hand-coded delivery, and spreadsheet-based planning. New tools can compress parts of the lifecycle, but architecture, stakeholder alignment, and trade-off decisions still require people. This blog explains what should change and what should not.

AI-Augmented Data Engineering: What Is Actually Possible data engineering blog cover

March 10, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

AI-Augmented Data Engineering: What Is Actually Possible

AI cannot run a data engineering program on its own. It can accelerate specific stages such as discovery, scoring, documentation, conversion, and validation. This blog explains what is actually possible across the lifecycle and where senior engineering judgment remains essential.

What Distinguished-Grade AI Accelerators Look Like in Data Engineering data engineering blog cover

March 9, 2026

Hariharan Arulmozhi, Founder & CEO, 3X Data Engineering

What Distinguished-Grade AI Accelerators Look Like in Data Engineering

General-purpose AI tools improve individual developer productivity, but enterprise data engineering needs more than syntax generation. Distinguished-grade accelerators must handle dependencies, architecture-aware output, validation, domain patterns, secure deployment, and reproducible results. This blog explains what to look for.

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