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Data Infrastructure Setup
Data Infrastructure for Analytics & AI
Set up the data pipelines, storage, and governance needed for reliable analytics and AI. Build a scalable, secure foundation that turns your data into a strategic asset.
78%
of organizations struggle with data quality
5-10x
faster query performance with modern infrastructure
40-60%
reduction in data infrastructure costs
90%
of AI projects require quality data infrastructure
Build the Foundation for Data-Driven Decision Making
Modern businesses run on data, but most struggle with fragmented systems, poor data quality, and unreliable analytics. We build enterprise-grade data infrastructure that solves these challenges.
Unified Data Platform
Consolidate data from all sources into a single, reliable platform. Enable consistent analytics, reporting, and AI capabilities across your organization.
Enterprise-Grade Quality
Our infrastructure includes comprehensive governance, security, and quality controls. Your data remains accurate, compliant, and trustworthy at scale.
Scalable Data Architecture Design
We design modern data architectures that scale with your business growth and evolving analytics needs. Our architectures balance performance, cost, and flexibility using proven patterns like data mesh, data fabric, and medallion architecture. We ensure your infrastructure can handle increasing data volumes, new sources, and advanced use cases without requiring complete redesigns.
Enterprise Data Warehouses & Lakes
We implement modern data warehouses and lakes using industry-leading platforms like Snowflake, BigQuery, Redshift, and Databricks. Our implementations support complex analytics, machine learning workloads, and high-concurrency querying while maintaining performance and cost efficiency. We design schemas optimized for your specific reporting and analytics use cases.
Robust ETL/ELT Pipelines
We build reliable, maintainable data pipelines that extract data from source systems, transform it for analytics, and load it into your warehouse or lake. Our pipelines include comprehensive error handling, retry logic, monitoring, and alerting to ensure data flows reliably. We use modern tools like Fivetran, Airbyte, dbt, and custom code when needed.
Comprehensive Governance & Security
We implement enterprise-grade data governance ensuring your data remains secure, compliant, and trustworthy. This includes role-based access controls, data classification and tagging, audit logging, encryption at rest and in transit, and compliance frameworks for GDPR, CCPA, HIPAA, and other regulations. We help you maintain data quality and trust while meeting regulatory requirements.
Trusted by Data-Driven Organizations
Real Data Infrastructure Results
See how we've helped organizations build scalable, reliable data platforms that enable advanced analytics and AI.
Retail & E-commerce
E-Commerce Analytics Platform
RetailMax Corporation
Built a comprehensive data infrastructure consolidating data from e-commerce platform, ERP, marketing tools, and customer service systems. Implemented real-time inventory tracking, customer 360-degree views, and advanced product recommendation engine.
20x faster
Query Performance
95% automated
Data Processing
+340%
Analytics Adoption
Technologies
SnowflakeReal-time PipelinesData Governance
Our Data Infrastructure Setup Process
A proven methodology that ensures successful implementation and adoption
1
1-2 weeks
Discovery & Assessment
Comprehensive assessment of your current data landscape including source systems, data volumes, quality, usage patterns, and pain points. We document your analytics requirements, compliance needs, and growth projections to inform architecture decisions.
Deliverables
Data source inventoryCurrent state assessmentRequirements documentation
2
2-3 weeks
Architecture Design
Design your target data architecture including warehouse/lake selection, pipeline architecture, data modeling approach, security framework, and scalability strategy. We create detailed technical specifications and get stakeholder alignment before implementation.
Deliverables
Architecture diagramsTechnology selectionData model design
3
1-2 weeks
Infrastructure Provisioning
Set up your cloud infrastructure including data warehouse/lake, compute resources, storage, networking, and security configurations. We use infrastructure-as-code for repeatability and establish monitoring and alerting from day one.
Deliverables
Cloud infrastructureSecurity configurationMonitoring setup
4
3-6 weeks
Pipeline Development
Build and test data pipelines for each source system including extraction logic, transformation rules, data quality checks, and error handling. We implement both initial historical loads and ongoing incremental updates with comprehensive logging.
Deliverables
ETL/ELT pipelinesData quality rulesTesting results
5
2-3 weeks
Governance Implementation
Implement data governance framework including access controls, data cataloging, lineage tracking, quality monitoring, and compliance controls. We establish policies, procedures, and documentation for ongoing governance.
Deliverables
Access controlsData catalogGovernance policies
6
2-3 weeks
Migration & Launch
Execute data migration, validate data accuracy through reconciliation, conduct user acceptance testing, and provide training. We perform parallel runs to ensure reliability before cutting over to the new infrastructure.
Deliverables
Migrated dataValidation reportsTraining materials
Complete Data Infrastructure Deliverables
Everything you need for production-ready data infrastructure with ongoing reliability
Data Warehouse/Lake
Fully configured and optimized data warehouse or data lake on your chosen platform (Snowflake, BigQuery, Redshift, Databricks, or Azure Synapse) with proper security, backup, and monitoring.
Production Data Pipelines
Automated ETL/ELT pipelines for all data sources with error handling, retry logic, data quality checks, and comprehensive logging for easy troubleshooting.
Data Models & Schemas
Optimized data models designed for your analytics use cases including dimensional models, fact tables, and optimized query patterns for maximum performance.
Governance Framework
Complete data governance implementation including role-based access controls, data catalog, lineage tracking, quality monitoring, and compliance controls.
Documentation
Comprehensive documentation covering architecture, data models, pipeline specifications, governance policies, runbooks, and troubleshooting guides.
Monitoring & Alerting
Configured monitoring dashboards and alerting for pipeline health, data quality issues, performance degradation, and security events.
Security Configuration
Enterprise-grade security including encryption at rest and in transit, network security, identity management, audit logging, and compliance controls.
Infrastructure as Code
All infrastructure defined as code (Terraform, CloudFormation, or ARM templates) for version control, repeatability, and disaster recovery.
Training & Knowledge Transfer
Hands-on training for your team covering infrastructure usage, pipeline maintenance, adding new sources, troubleshooting, and best practices.
Related Services
Explore other services that work together with your data infrastructure
Digital Transformation
CRM & ERP Integration
Connect your CRM, ERP, and core platforms for unified data and seamless real-time operations.
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Digital Transformation
Digital Strategy Consulting
Align technology investments with business objectives through strategic roadmaps and prioritization frameworks.
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Digital Transformation
Process Optimization
Eliminate bottlenecks and automate workflows to improve operational efficiency and reduce costs.
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Digital Transformation
Custom Enterprise Tools
Build bespoke enterprise software that matches your unique workflows, rules, and security needs.
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Web Development
API Development & Integration
Connect systems and build robust APIs that power modern digital ecosystems.
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Web Development
Custom Web Applications
Build powerful, scalable web applications tailored to your unique business requirements.
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What Our Clients Say
Real feedback from organizations we've helped transform with modern data infrastructure
Data Infrastructure Setup
“Verlua transformed our fragmented data landscape into a unified, reliable infrastructure. Our analytics teams can now access clean data in real-time, and our data quality has improved dramatically. The implementation was seamless.”
David Kim
Chief Data Officer at RetailMax Corporation
Healthcare Data Infrastructure
“The team delivered a HIPAA-compliant data warehouse that exceeded our expectations. Their expertise in healthcare data governance and security gave us confidence, and the performance improvements have enabled entirely new analytics capabilities.”
Dr. Sarah Martinez
VP of Technology at MedTech Solutions
Financial Data Lake
“Outstanding work on our enterprise data lake. They integrated 50+ data sources, implemented robust governance, and delivered ahead of schedule. Our fraud detection accuracy has improved significantly, and we are saving millions in infrastructure costs.”
James Thompson
Head of Data Engineering at Global Finance Group
Frequently Asked Questions
Everything you need to know about data infrastructure setup services
What is data infrastructure and why do I need it?
Data infrastructure is the foundation that enables organizations to collect, store, process, and analyze data effectively. It includes data warehouses, pipelines, governance frameworks, and access controls. You need it to ensure data quality, enable reliable analytics, support AI initiatives, and maintain compliance with data regulations. Without proper infrastructure, data becomes siloed, unreliable, and difficult to leverage for business insights.
How long does it take to set up data infrastructure?
A typical data infrastructure setup takes 8-16 weeks depending on complexity, data sources, and requirements. Simple implementations with a few data sources and basic reporting can be completed in 6-8 weeks. Complex enterprise implementations with multiple systems, real-time pipelines, and advanced governance may take 12-20 weeks. We provide a detailed timeline during our discovery phase based on your specific needs.
What is the difference between a data warehouse and a data lake?
A data warehouse stores structured, processed data optimized for querying and reporting. It uses a predefined schema and is ideal for business intelligence and analytics. A data lake stores raw data in its native format (structured, semi-structured, and unstructured) without requiring a predefined schema. It is ideal for big data processing, machine learning, and exploratory analytics. Many organizations use both in a modern data architecture.
Can you integrate with our existing systems and databases?
Yes! We specialize in integrating data infrastructure with existing systems including CRMs (Salesforce, HubSpot), ERPs (SAP, Oracle, NetSuite), databases (MySQL, PostgreSQL, SQL Server, MongoDB), cloud platforms (AWS, Azure, GCP), marketing tools, and custom applications. We build connectors and pipelines that extract, transform, and load data from any source into your centralized infrastructure.
What data governance features do you implement?
We implement comprehensive data governance including data cataloging and metadata management, role-based access controls (RBAC), data lineage tracking, quality monitoring and validation rules, compliance frameworks (GDPR, CCPA, HIPAA), audit logging and change tracking, data masking and encryption, and retention policies. These ensure your data remains secure, compliant, and trustworthy.
Do you support real-time data processing?
Yes! We implement both batch and real-time (streaming) data pipelines depending on your needs. Real-time pipelines use technologies like Apache Kafka, AWS Kinesis, or Azure Event Hubs to process data as it arrives. This enables use cases like real-time dashboards, fraud detection, live recommendations, and operational monitoring. We help you determine which data sources need real-time processing versus scheduled batch updates.
What cloud platforms do you work with?
We have expertise across all major cloud platforms: AWS (Redshift, S3, Glue, Kinesis, Lake Formation), Azure (Synapse Analytics, Data Factory, Data Lake Storage), and Google Cloud Platform (BigQuery, Dataflow, Cloud Storage). We also work with cloud-agnostic tools like Snowflake, Databricks, and Fivetran. We recommend the best platform based on your existing infrastructure, budget, and requirements.
How do you ensure data quality and reliability?
We implement multi-layered data quality controls including automated validation rules at ingestion, data profiling and anomaly detection, schema enforcement and type checking, duplicate detection and deduplication, referential integrity checks, monitoring and alerting for pipeline failures, and reconciliation reports between source and target. We also establish data quality metrics and SLAs to maintain high reliability over time.
Can you help with data migration from legacy systems?
Absolutely! We specialize in migrating data from legacy systems to modern infrastructure. Our process includes thorough data assessment and mapping, cleansing and transformation of historical data, parallel run validation to ensure accuracy, incremental migration to minimize disruption, rollback plans for risk mitigation, and comprehensive testing before cutover. We ensure zero data loss and minimal downtime during migration.
What ongoing support do you provide after implementation?
We provide comprehensive ongoing support including monitoring and alerting for pipeline health, performance optimization and scaling, new data source integration, schema evolution and migration, troubleshooting and issue resolution, documentation updates, training for your team, and regular reviews of infrastructure efficiency. We offer flexible support plans from on-demand assistance to fully managed services depending on your needs.
Ready to Build a Modern Data Infrastructure?
Let's create a scalable, reliable data foundation that enables advanced analytics, AI capabilities, and data-driven decision making across your organization.