AWS Professional Services • Data, Analytics & AI

Build a trusted data foundation for analytics, machine learning and AI

Yaqeen helps organizations modernize data platforms, unify fragmented information, create governed analytics and implement machine learning and AI solutions on AWS—turning data into operational insight, automation and better decisions.

Data Modernization

Business Intelligence

Machine Learning

AI-Ready Architecture

Data-to-Intelligence Blueprint

GOVERNED & SCALABLE

TRUSTED DATA FOUNDATION

Unified

Business data

Faster

Decision-making

Smarter

Automation

Secure

Data governance

Ingest

Applications, files, APIs and streams

Govern

Quality, catalog, lineage and access

Analyze

Dashboards, metrics and insights

Intelligize

ML, GenAI and intelligent workflows

Move from fragmented data to trusted intelligence

Analytics and AI only create value when data is accessible, governed, timely and connected to real business decisions and workflows.

Create the data foundation needed for reporting, prediction and intelligent automation

Organizations often struggle with disconnected systems, manual reporting, inconsistent definitions, limited data quality and difficulty scaling analytics. These issues become even more important when machine learning and generative AI are introduced.

Yaqeen designs practical AWS data architectures that support ingestion, storage, transformation, governance, analytics and AI. We help prioritize high-value use cases, establish trusted data products and deliver insights through dashboards, applications, APIs and automated workflows.

Business-first use cases

Prioritize analytics and AI initiatives with clear users, decisions and measurable value.

Trusted data

Improve quality, definitions, access, lineage, governance and accountability.

Scalable AWS architecture

Use secure, flexible services for batch, streaming, structured and unstructured data.

Operational adoption

Deliver intelligence inside dashboards, applications and day-to-day workflows.

What we address

Scope is tailored to current data maturity, business priorities, source systems and regulatory requirements.

Data strategy and use cases

Business priorities, decision needs, metrics, AI opportunities and delivery roadmap.

Data platform architecture

Ingestion, storage, transformation, integration, semantic layers and consumption patterns.

Governance and security

Ownership, cataloging, access, privacy, quality, lineage and compliance controls.

Analytics and visualization

Operational dashboards, executive reporting, self-service analytics and embedded insights.

Machine learning and AI

Predictive models, intelligent automation, AI applications and responsible deployment.

Core data, analytics and AI capabilities

Focused services that span strategy, architecture, engineering, visualization, machine learning and operationalization.

Data & AI Strategy

Define high-value use cases, target capabilities, governance priorities and an executable roadmap.

Use-case discovery and prioritization
Data and AI readiness assessment
Business case and delivery roadmap

Data Platform Modernization

Design and implement scalable AWS data platforms for analytics, applications and AI.

Data lake and lakehouse architecture
Warehouse and data-mart modernization
Batch and streaming ingestion

Data Integration & Engineering

Connect source systems, automate pipelines and create reusable trusted datasets.

ETL and ELT pipelines
API, file and event integration
Data transformation and orchestration

Analytics & Business Intelligence

Deliver dashboards, reporting and embedded analytics that support operational and executive decisions.

Amazon QuickSight solutions
KPI and semantic-model design
Self-service and embedded analytics

Machine Learning & Predictive Analytics

Develop and operationalize models for forecasting, risk, classification, optimization and next-best action.

Feature and model development
Training, evaluation and deployment
MLOps and model monitoring

AI-Enabled Applications

Integrate intelligent search, recommendations, summarization and workflow automation into business applications.

AI application architecture
Knowledge and retrieval patterns
Human oversight and operational controls

Data-to-Value Approach

A structured path from use-case discovery to operational intelligence

Yaqeen combines business alignment, data architecture, engineering, analytics, AI development and production adoption.

Discover

Define users, business decisions, pain points, data sources and measurable outcomes.

Assess

Evaluate data quality, architecture, governance, security, skills and AI readiness.

Architect

Design ingestion, storage, transformation, governance, analytics and AI patterns.

Build

Implement pipelines, data products, dashboards, models and intelligent applications.

Validate

Test data quality, model performance, usability, security and business impact.

Operate & Improve

Monitor pipelines, data quality, models, costs, adoption and evolving business needs.

High-value data, analytics and AI use cases

Solutions are tailored to industry, workflow and data maturity rather than limited to a single technology pattern.

Executive & Operational Dashboards

Unified Performance Insight

Bring together financial, operational, customer and service metrics in governed dashboards.

Customer & Patient Intelligence

Better Segmentation

Create longitudinal views, cohorts, risk indicators and personalized engagement insights.

Forecasting & Predictive Analytics

Anticipate Outcomes

Predict demand, risk, utilization, revenue, staffing or operational performance.

Compliance & Quality Analytics

Improve Oversight

Automate monitoring, scoring, anomaly detection and evidence-based review.

Intelligent Document Processing

Extract Structured Insight

Process forms, reports, correspondence and unstructured records for downstream workflows.

AI Search & Knowledge Assistants

Find Answers Faster

Provide secure, grounded access to organizational policies, documents and operational knowledge.

Recommendation & Next-Best Action

Guide Decisions

Use data and models to recommend interventions, outreach, priorities or follow-up actions.

AI-Enabled Workflow Automation

Reduce Manual Effort

Embed classification, summarization, routing and decision support into business processes.

Choose the right data, analytics and AI engagement

Start with strategy and readiness, validate a priority use case or implement a broader data and AI program.

Data & AI Readiness Assessment

Identify the highest-value use cases and the foundation required to deliver them

A focused assessment evaluates business priorities, source data, architecture, governance, skills and readiness for analytics and AI.

Best for

Organizations with fragmented data, manual reporting or growing interest in AI.

Typical outputs

Prioritized use cases, readiness findings, architecture recommendations and delivery roadmap.

Common focus areas

Business value, data quality, governance, security, analytics maturity and AI feasibility.

Modern Data Foundation

Build the governed AWS platform required for analytics and AI

This engagement implements ingestion, storage, transformation, cataloging, access and reusable data products on AWS.

Best for

Organizations whose current data environment limits reporting, integration or AI adoption.

Typical outputs

AWS data architecture, pipelines, governed datasets, security controls and operational documentation.

Common focus areas

Data lake, warehouse, integration, quality, governance, cataloging and cost management.

Analytics or AI Pilot

Validate a focused use case with real data and measurable outcomes

A pilot delivers a dashboard, predictive model or intelligent application to test feasibility, usability and business value.

Best for

Organizations that want to prove value before scaling analytics or AI investment.

Typical outputs

Working pilot, architecture, evaluation results, adoption findings and production roadmap.

Common focus areas

Data preparation, dashboards, model quality, user workflow, security and operational fit.

Enterprise Data & AI Program

Scale trusted data, analytics and AI across multiple business domains

A coordinated program combines platform modernization, governance, data products, analytics, ML and AI-enabled applications.

Best for

Organizations with multiple use cases, business units and long-term data transformation goals.

Typical outputs

Enterprise platform, governed data products, dashboards, models, AI solutions and operating model.

Common services

Program governance, architecture, engineering, adoption, MLOps, security and managed operations.

Business outcomes

Data, analytics and AI investments should improve decisions, reduce manual effort and create measurable operational value.

Trusted

Business data

Create governed, reusable data products and consistent performance measures.

Faster

Decision-making

Deliver timely insight through dashboards, alerts and embedded analytics.

Smarter

Automation

Use models and AI to classify, predict, summarize, recommend and route work.

Scalable

Data & AI foundation

Support future analytics and intelligent applications without rebuilding the platform.

Related AWS professional services

Data and AI initiatives often connect directly to application modernization, generative AI, security and managed operations.

Generative AI & Agentic AI

Build secure generative AI assistants, workflow agents and intelligent experiences using trusted data.

Application Modernization

Embed analytics and AI capabilities into modern applications, APIs and cloud-native workflows.

AWS Cloud Operations

Operate data platforms, dashboards, models and AI workloads with monitoring, governance and optimization.

Ready to turn your data into analytics and AI outcomes?

Start with a data and AI readiness assessment, foundation engagement or focused pilot tied to a measurable business use case.