Skip to content
Close
SEARCH
Contact Us
Contact Us
  • Data_Platform_Moderniszation _and Lakehouse_v6_1750x875_1x

    Data Platform Modernization & Lakehouse

    A governed lakehouse ready for analytics and AI.

Overview

Data Platform Modernization and Lakehouse designs and implements modern enterprise data platforms on Snowflake, Databricks, Microsoft Fabric, and cloud-native lakehouse architectures, unifying structured and unstructured data under consistent governance. Accion Labs modernizes fragmented estates into a single governed lakehouse that improves performance and cost, and gives analytics and AI the foundation they depend on.

The Challenge

Legacy warehouses and fragmented data lakes were never built for modern analytics and AI. Data is duplicated across systems, governance is applied inconsistently or not at all, and structured and unstructured data sit in separate silos that AI cannot use together. As workloads grow, cost scales faster than the value they return, and the platform becomes a constraint rather than a foundation. The challenge is unifying that estate into one governed, cost-efficient platform that analytics and AI can actually build on.

What We Deliver

  • A governed cloud-native lakehouse. A modern platform on Snowflake, Databricks, or Microsoft Fabric, with governance applied consistently.

  • Unified structured and unstructured data. One foundation that brings previously siloed data together for analytics and AI.

  • Better performance and cost. A platform tuned so performance improves and cost scales with value rather than ahead of it. 

How We Do It

Modernization is sequenced from the readiness assessment and grounded in your real estate, so migration is de-risked and cost is understood before workloads move.

Target architecture

Define the lakehouse target on Snowflake, Databricks or Fabric.

Migrate in waves

Move workloads in sequenced waves with complexity and risk mapped.

Unify

Unify structured and unstructured data under consistent governance.

Optimize

Tune performance and cost as workloads land.

What We Assess

Data platform and architecture

Data Platform and Architecture

Sources, ingestion, storage, processing, and serving layers, and how well they support analytics and AI workloads.

pipeline and integration

Pipelines and Integration

Batch, streaming, and change-data-capture pipelines, orchestration, and schema management.

Data quality and observability

Data Quality and Observability

Validity, accuracy, and completeness, quality thresholds, lineage, and monitoring.

Governace security and access

Governance, Security, and Access

Ownership, policies, cataloging, role-based access, masking, and compliance readiness.

Entrprise Data model

Enterprise Data Model

Master data, canonical models, and how consistently data is defined across core and non-core applications.

Cost and FinOps

Cost and FinOps

Current run cost, storage tiering, and workload efficiency, and where modernization can reduce spend.

AI GenAI Readiness

AI and GenAI Readiness

Feature stores, semantic and metrics layers, and the governed foundations that AI and GenAI applications depend on.

What You Get 

A governed cloud-native lakehouse 

Unified structured and unstructured data 

Wave-based, de-risked migration 

Improved performance and cost efficiency 

An AI-ready data foundation 

Key Accelerators 

SKG

Provides one governed, queryable knowledge graph for every agent. 

KAPS

Runs analytics over a governed data layer, so insight is traceable. 

Modernizing Church Curriculum Management for Widespread Influence
01

Automated estate assessment that scans platforms and pipelines with dependency mapping

02

Dashboard-based sizing that reduces migration risk before a single workload moves

03

Metadata-driven analysis that grounds the roadmap in the real environment

Business Outcomes

01

A governed, AI-ready lakehouse

02

Improved performance and cost efficiency

03

De-risked, wave-based migration

04

A foundation every workload can build on

Why Accion

Semantic Engineering at the core

Deterministic, explainable AI grounded in your enterprise knowledge, not generic models.

Engineering depth

Decades of product, platform and data engineering behind every AI build.

Outcome-led delivery

Measurable business impact, not proofs of concept that stall before production.

Certified across platforms

Partner-certified on Microsoft, AWS, Salesforce, ServiceNow, Snowflake and Databricks, with production delivery on each.

Governed by design

Security, compliance and Responsible AI built in from the first sprint. 

Migration de-risked before it starts

We sequence modernization from the readiness assessment and ground it in your real estate, so complexity and cost are understood. 

Why Accion

Semantic Engineering at the core

Deterministic, explainable AI grounded in your enterprise knowledge, not generic models.

Engineering depth

Decades of product, platform and data engineering behind every AI build.

Outcome-led delivery

Measurable business impact, not proofs of concept that stall before production.

IPs and accelerators

AI Prism, BreezeAI, ASIMOV, SPEX and more shorten time to value.

Governed by design

Security, compliance and Responsible AI built in from the first sprint.

Relevant Links

Modernize to a governed lakehouse built for AI.

Request for Services

FAQs

Data platform modernization involves designing and implementing a modern, governed lakehouse on Snowflake, Databricks, or Microsoft Fabric that unifies structured and unstructured data for analytics and AI.

We sequence migration based on the readiness assessment and ground the plan in your existing data estate, so complexity, dependencies, and cost are understood before any workload moves.

We work with Snowflake, Databricks, Microsoft Fabric, and cloud-native lakehouse architectures, with certified delivery capabilities across these platforms.