Data & Integration

Connect Data. Build Intelligence. Accelerate AI.

Build governed data platforms, lakehouse foundations, real-time data engineering, APIs, event-driven integration, semantic layers, and reusable data products for analytics and AI.

The Enterprise Challenge

Create Trusted Data and Integration Foundations at Enterprise Scale

Enterprise analytics and AI depend on trusted data and dependable integration. EverestDX connects modern data platforms, APIs, events, pipelines, governance, quality, and semantics into an architecture designed for reliable reuse across analytics, applications, and AI.

Offerings

Six Data & Integration Offerings

Connect trusted data, modern platforms, integration, governance, and semantics across analytics, applications, and AI.

01 / Data platforms & lakehouse

Modern Data Platforms & Lakehouse

Engineer lakehouse and warehouse platforms.
Use open table formats and cloud-native architecture.
Optimize performance, scale, and platform economics.

Accelerated by DatamutationX

01 / INSIDE THE OFFERING

Modern Data Platforms & Lakehouse

We design and engineer modern lakehouse and analytical platforms that support BI, data engineering, operational analytics, and AI while preserving openness, governance, and workload flexibility.

BUSINESS OUTCOME

Create a scalable, governed data foundation that supports analytics and AI without repeated re-platforming.

02 / Engineering & streaming

Data Engineering & Real-Time Streaming

Build batch, CDC, and streaming ingestion pipelines.
Automate transformation, testing, and observability.
Operate reliable data pipelines at enterprise scale.

Accelerated by DatamutationX

02 / INSIDE THE OFFERING

Data Engineering & Real-Time Streaming

We build batch, CDC, and real-time pipelines with reusable transformation patterns, automated data testing, observability, and operational controls so trusted data reaches consumers consistently.

BUSINESS OUTCOME

Improve freshness, reliability, and time to trusted data across enterprise workloads.

03 / APIs & event integration

Enterprise Integration, APIs & Event Architecture

Modernize application, API, messaging, and event integration.
Standardize orchestration, security, and reusable connectors.
Support B2B, file, workflow, and AI/agent connectivity.

03 / INSIDE THE OFFERING

Enterprise Integration, APIs & Event Architecture

We modernize point-to-point integration into governed API, event, messaging, workflow, B2B, and data-integration patterns that connect enterprise applications without creating another layer of brittle custom interfaces.

The eight integration disciplines

Data integration – ETL/ELT, CDC, and data movement across systems.
Application integration (iPaaS/ESB) – process orchestration and system integration.
API integration & management – design, gateway, security, and developer portal.
Event streaming – real-time ingestion, stream processing, and schema governance.
Enterprise messaging – reliable, secure asynchronous messaging and queues.
Workflow & orchestration – automation, scheduling, and human-in-the-loop steps.
B2B & file integration – EDI/AS2, SFTP, and partner management.
AI integration & agent connectivity – LLM/model access, AI gateway, and agent orchestration.

BUSINESS OUTCOME

Reduce integration complexity while improving reuse, resilience, governance, and delivery speed.

Connected digital data and technology layers. — CONNECTED ENTERPRISE FOUNDATIONSConnected data.
Shared intelligence.
Make trusted data work across your enterprise.

04 / Governance & quality

Data Governance, Quality & Observability

Establish catalog, lineage, ownership, and stewardship.
Continuously monitor quality, freshness, and pipeline health.
Apply privacy, access, and policy controls.

04 / INSIDE THE OFFERING

Data Governance, Quality & Observability

We operationalize governance through metadata, lineage, ownership, data quality, observability, access control, and policy so trusted data can be discovered and reused across analytics and AI.

BUSINESS OUTCOME

Increase trust, accountability, and reuse across critical enterprise data domains.

06 / Strategy & architecture

Data Strategy & Platform Architecture

Assess data, integration, governance, and operating-model maturity.
Design target platform and integration architecture.
Sequence the roadmap around business value and dependencies.

06 / INSIDE THE OFFERING

Data Strategy & Platform Architecture

We align platform, integration, governance, semantic, and operating-model decisions into an executable data architecture and roadmap grounded in the enterprise’s current estate and priorities.

BUSINESS OUTCOME

Align data investment, architecture, governance, and delivery around a clear transformation roadmap.

Use Cases

Where This Solution Creates Value

Representative enterprise use cases that connect the capability to a concrete business and operating outcome.

01Trusted data, ready to reuse

Modern Lakehouse & Data Products

Create governed lakehouse and reusable data-product foundations for analytics, reporting, applications, and AI-ready consumption.

Business outcome

Faster access to trusted, reusable enterprise data.

02From events to real-time insight

Real-Time Data & Streaming

Ingest and process events, CDC, telemetry, and operational data with governed streaming and real-time transformation patterns.

Business outcome

Improve freshness, reliability, and time to trusted data.

03Connect once. Reuse everywhere.

API & Event Integration Modernization

Replace brittle point-to-point interfaces with governed APIs, events, messaging, reusable connectors, and orchestration patterns.

Business outcome

Faster integration delivery and lower operational complexity.

04A shared understanding of data

Data Governance & Semantic Intelligence

Connect cataloging, lineage, quality, ownership, semantic definitions, and data products into a governed consumption layer.

Business outcome

More consistent decisions with less reconciliation across teams.

ENABLEMENT ACCELERATORS

Accelerators That Speed Up Transformation

EverestDX proprietary frameworks and automation that accelerate data & integration delivery while complementing the core consulting offerings and product portfolio.

Data Transformation Accelerator

DatamutationX — Data Transformation

Intelligent data transformation automation for faster migration, modernization, pipeline generation, and data-quality execution at scale.

Automated code translation & migration

Data quality validation & profiling

Rule extraction & mapping

End-to-end pipeline generation

Performance & cost optimization

Reusable accelerators & templates

Best fit: Data-platform modernization · ETL/ELT migration · Lakehouse adoption · Legacy transformation · AI data readiness

Accelerators are EverestDX delivery IP—not additional products in the CORA / OPTIX / InsightONE / BotX portfolio.

PRODUCT & PLATFORM ENABLEMENT

Product-backed Data & Integration

VantageX, CORA, and OPTIX reinforce the data solution where enterprise context, conversational intelligence, or platform economics add differentiated value.

Primary enablement

VantageX + CORA

Enterprise context and conversational intelligence

VantageX connects enterprise entities, relationships, services, ownership, and data context; CORA provides natural-language discovery, analysis, and decision support.

Unified enterprise context
Semantic and relationship intelligence
Natural-language discovery
Role-aware enterprise insight

Solution enabler

Data cost & optimization

OPTIX

Data platform cost intelligence

OPTIX connects data-platform consumption, workload behavior, business ownership, and cost to optimization opportunities across major analytical platforms.

Workload cost visibility
Usage attribution
Optimization opportunities
Budget and consumption insight

Solution enabler

CONNECTED TECHNOLOGY

Technology Ecosystem

Representative platforms and technologies commonly used across these solution engagements.

Microsoft Azure
Power BI
Informatica
MuleSoft

Representative Outcomes

Outcomes We Design For

Illustrative outcomes from this type of transformation. Specific results depend on scope, baseline, environment, and execution.

⏱

Faster Data Onboarding

Reusable engineering patterns shorten the path from source onboarding to trusted consumption.

✓

Higher Data Trust

Governance, quality, lineage, and ownership make critical data easier to trust and reuse.

⇄

Connected Ecosystem

APIs, events, and orchestration reduce point-to-point integration complexity.

◎

More Consistent Decisions

Shared metrics and semantic models reduce reconciliation across analytics and business teams.

FAQ

Common Questions

Do we need to replace our existing data warehouse?

Not necessarily. We typically modernize incrementally by connecting, extending, or migrating the workloads where a new architecture creates clear value rather than forcing a full replacement on day one.

How do you handle legacy application integration?

We assess existing interfaces and modernize them into governed API, event, messaging, managed-connector, or data-integration patterns based on workload requirements and operational risk.

How do you phase a data platform modernization?

We usually organize delivery by domain or high-value workload, establishing the platform, governance, integration, and consumption patterns needed for that scope before expanding them across the enterprise.

Enterprise Trust