AI‑Ready Data Platforms

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Modern Data Platforms for Cloud & AI

I help small and medium companies migrate legacy systems to the cloud and build modern, governed, AI‑ready data platforms.

Whether you are stuck with legacy systems, slow pipelines, or high cloud costs, I design and deliver platforms that are scalable, secure, and ready for AI workloads like RAG, vector search, and advanced analytics.

Targeting: Small & Medium Companies

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Service Packages I Offer

Targeting: Small & Medium Companies

⭐ 1. Data Platform Setup

Build the core foundation for a scalable, secure, cloud‑native data platform.

What I Deliver

New Databases & Data Stores — Design and deploy relational/NoSQL databases optimized for analytics and operational workloads.
Cloud‑Native Platform (AWS / Azure / GCP) — End‑to‑end setup of storage, compute, networking, security, and monitoring.
Databricks Lakehouse Setup — Workspaces, clusters, SQL Warehouses, Unity Catalog, Delta Lake, and Medallion architecture (Bronze → Silver → Gold).
Security, RBAC & Governance — Access control, lineage, cataloging, audit logs, and compliance‑aligned governance.

Outcome — A ready‑to‑use, enterprise‑grade data platform supporting analytics, reporting, and AI workloads.

⭐ 2. Data Modernization & Migration

Transform legacy systems into modern, cloud‑native platforms with measurable performance and cost benefits.

What I Deliver

Legacy → Cloud Migration — Move databases, ETL workloads, and reporting systems to AWS/Azure/GCP with minimal disruption.
1. SQL Server → PostgreSQL (Aurora/RDS/similar)
2. Oracle → PostgreSQL (Aurora/RDS/similar)
3. {any database} → AWS Redshift
4. {any database} → Snowflake
5. Snowflake → Databricks
Workload Optimization — Improve performance, reduce latency, and eliminate bottlenecks in pipelines and queries.
Cost Reduction & Tuning — Optimize compute/storage usage, cluster sizing, and workload scheduling to reduce cloud spend.

Outcome — A faster, cleaner, cost‑efficient platform that eliminates technical debt and supports future AI adoption.

⭐ 3. Data Engineering

Automate and scale your data operations for analytics, BI, and real‑time insights.

What I Deliver

ETL/ELT Pipelines (Batch + Streaming) — Ingestion from databases, APIs, SaaS apps, files, and real‑time sources.
Data Quality & Transformation — Automated validation, cleansing, and transformation into BI‑ready datasets.
CI/CD & Infrastructure‑as‑Code — Automated deployments, versioning, and environment consistency using Terraform, GitHub Actions, or Azure DevOps.

Outcome — Reliable, automated pipelines that deliver trusted data to analytics, dashboards, and AI systems.

⭐ 4. AI/ML Enablement

Prepare your data platform for real‑world AI adoption, automation, and intelligent decision‑making.

I specialize in building the foundational components required for AI systems to work reliably in production.

My experience includes hands‑on POC development and early‑stage implementations, and I am now focused on delivering real‑time, production‑grade AI solutions for small and mid‑size companies.

What I Deliver

Data preparation Pipelines for AI
Clean, structured, high‑quality datasets optimized for LLMs, embeddings, and model training.
Chatbot workflow automation
Build domain‑specific chatbots that integrate with your data, documents, and business processes
RAG‑Driven Decision Summaries
Generate automated summaries, insights, and recommendations from enterprise data and documents.

Outcome — Enables production‑ready AI with clean data, RAG search, automated insights, and domain chatbots delivering accurate, real‑time intelligence for business decisions.

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Problems I Solve

Siloed and fragmented data systems
Slow and unreliable pipelines
Lack of governance and data trust
High cloud costs
No AI readiness

The Problem with Today’s Platforms

Siloed data across legacy systems
Slow, fragile ETL pipelines
No lineage, glossary, or governance
High cloud cost due to inefficient workloads
Manual reporting and inconsistent KPIs
Limited support for AI/ML workloads

Consequences: slow decisions, compliance risk, operational inefficiency, and inability to adopt AI.

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Value I Deliver

25–35% cost reduction
30–40% performance improvement
Faster analytics & decision‑making
Improved data quality and trust
Compliance readiness
AI‑ready data foundation

Why Companies Must Move to AI‑Ready Data Platforms

Automate knowledge retrieval with RAG + LLMs
Reduce manual reporting and accelerate insights
Build predictive and prescriptive analytics
Enable governance & improve data quality and trust

AI is only as strong as the data foundation beneath it, and most companies are not ready.

What an AI‑Ready Platform Requires

Modern Lakehouse / Warehouse architecture
Automated ingestion & transformation, clean and governed data
Modern tools for metadata, lineage, glossary, and catalog integration
Secure RBAC, audit controls, and compliance alignment

This is the blueprint for AI‑driven operations.

Book a 30‑minute consultation View service packages

Who I Am

I am a Cloud Data Architect with 15+ years of experience designing and modernizing enterprise data platforms across AWS and Azure.

My expertise includes:

Lakehouse & Warehouse architectures
Multi‑cloud migrations & integration
High‑performance ETL/ELT engineering
Data governance, lineage and metadata frameworks
AI/ML enablement (RAG, MLflow, vector search)

Why Work With Me?

Faster delivery, direct execution, and cost‑effective solutions compared to large consulting firms. I work hands‑on, with clear communication and a focus on measurable outcomes.

Why Now – Market Shift

AI is reshaping every industry. But AI only succeeds when the underlying data platform is modern, governed, and high quality.

AI/ML adoption is accelerating across all sectors
Legacy systems cannot support vector search, embeddings, or real‑time analytics
Lakehouse architectures are becoming the enterprise standard
Governance, lineage, and compliance requirements are tightening
Business teams demand faster, cleaner, more reliable data

Companies that delay modernization face higher costs, slower decisions, and an inability to adopt AI.

Governance & Regulatory Requirements

Data quality standards, glossary alignment
MDM and semantic consistency
Metadata & lineage (Collibra, Alation, Unity Catalog)
Access controls, RBAC, audit trails
Regulatory frameworks (SOX, HIPAA, GDPR)

Governance is the foundation of trust, compliance, and AI readiness.

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Case Examples

Case 1

Fragmented data platform → Built Lakehouse architecture → Reduced cost by 25–35% and improved reporting speed.

Case 2

Legacy systems → Cloud migration → Improved performance by 30–40% and enabled faster decision‑making.

Book a 30‑minute consultation View service packages

Let’s Modernize Your Data Platform

If your organization needs to migrate, modernize, or prepare for AI, I can help you deliver results quickly and confidently.

Share a brief description of your current data landscape and goals, and I’ll respond with a suggested approach.

Contact

Email: jacob.biguvu@gmail.com

LinkedIn: https://www.linkedin.com/in/biguvu/

Let’s Modernize Your Data Platform

If your organization needs to migrate, modernize, or prepare for AI, I can help you deliver results quickly and confidently.

Share a brief description of your current data landscape and goals, and I’ll respond with a suggested approach.

Contact

Email: jacob.biguvu@gmail.com

LinkedIn: https://www.linkedin.com/in/biguvu/