Data Warehouse Consulting & Implementation Case Studies

Finance and Banking Industry
Manufacturing Industry
Retail Industry

Our Data Warehouse Consulting Services

ExistBI provides end-to-end data warehouse consulting services covering strategy, architecture, implementation, migration, integration, modernisation and ongoing support. Our consultants work across cloud, hybrid and on-premise environments to help organisations create scalable, secure and high-performing data platforms for business intelligence, analytics and AI.

  • Data Warehouse Strategy & Architecture

  • Build a scalable data architecture aligned with your organisation’s business, analytics and technology objectives. ExistBI’s enterprise data warehouse consultants assess your existing data environment, identify architectural and integration requirements, and develop a practical roadmap for implementation or modernisation. We help define cloud, on-premise and hybrid architectures, technology platforms, data models, governance requirements and integration strategies designed to support current reporting needs while preparing your organisation for future analytics and AI initiatives.
  • Data Warehouse Implementation

  • ExistBI provides complete data warehouse implementation services, from initial architecture and data modelling through development, testing, deployment and production support. Our consultants design and implement enterprise data warehouses that consolidate information from ERP, CRM, finance, operational databases, cloud applications and other business systems. We develop the data pipelines, transformation processes, models and analytical structures required to deliver reliable, consistent and accessible information for reporting, business intelligence and advanced analytics.
  • Cloud Data Warehouse Migration

  • Modernise legacy data environments with our cloud data warehouse migration services. ExistBI helps organisations assess existing platforms, develop migration strategies and move data warehouse workloads to modern cloud technologies such as Microsoft Fabric, Azure, Snowflake, Amazon AWS and Google Cloud. Our consultants address architecture, data migration, ETL/ELT conversion, security, testing and performance optimisation while helping minimise disruption to existing reporting and analytics. We also support hybrid strategies where selected workloads remain on-premise.
  • ETL/ELT & Data Integration

  • Create reliable data pipelines that connect information across your enterprise. ExistBI provides data warehouse ETL/ELT consulting and implementation services for integrating data from databases, ERP and CRM platforms, APIs, cloud applications, files and other enterprise sources. Our consultants design, develop and optimise batch and cloud-based integration processes using technologies including Microsoft Fabric Data Factory, Azure Data Factory, Informatica, IBM DataStage and other leading integration platforms. We focus on data quality, reliability, scalability and maintainability throughout the integration lifecycle.
  • Data Modelling & Semantic Layers
  • Transform complex enterprise data into consistent, business-ready information. ExistBI designs dimensional models, analytical data structures and semantic layers that establish common definitions for business entities, relationships, measures and KPIs. A well-designed semantic layer provides users, BI applications and AI solutions with a governed and reusable view of enterprise data. Our consultants help organisations develop semantic models that improve reporting consistency, simplify analytics and create a trusted data foundation for Power BI, Microsoft Fabric and other analytical and AI platforms.
  • Data Warehouse Modernisation
  • Modernise legacy data warehouse environments to improve scalability, performance and support for modern analytics. ExistBI assesses existing architectures, ETL processes, databases, reporting dependencies and data models to identify opportunities for transformation. Our consultants help organisations migrate from legacy platforms, redesign data pipelines, introduce cloud and lakehouse technologies, and modernise analytical architectures while preserving critical business logic. Modernisation initiatives can also prepare enterprise data environments for self-service analytics, machine learning and generative AI applications.
  • Performance Optimisation
  • Improve the speed, efficiency and reliability of your existing data warehouse. ExistBI’s consultants analyse database performance, data models, queries, ETL/ELT pipelines, workloads, storage and reporting patterns to identify bottlenecks and optimisation opportunities. We help organisations improve query performance, reduce data processing times, optimise resource utilisation and address scalability challenges. Our performance tuning services can support cloud, hybrid and on-premise data warehouse environments and can be delivered as a focused optimisation engagement or as part of a broader modernisation initiative.
  • Managed Data Warehouse Support
  • Protect your data warehouse investment with ongoing technical support, monitoring and optimisation. ExistBI provides managed data warehouse support services for cloud, hybrid and on-premise environments, helping organisations maintain reliable data pipelines, resolve production issues, optimise performance and implement ongoing enhancements. Support can include ETL/ELT troubleshooting, database administration, data quality monitoring, platform upgrades, performance tuning and reporting support. Flexible SLA-based support models are available to complement your internal IT and data teams.

AI-Ready Data Warehouses & Semantic Layer Consulting

Build a Trusted Data Foundation for Enterprise AI

Successful AI initiatives depend on accurate, accessible and well-structured enterprise data.

ExistBI helps organisations modernise their data warehouse environments and develop the governed data foundations needed to support artificial intelligence, machine learning and advanced analytics.

Our consultants design and implement scalable data architectures that integrate information from enterprise applications, operational databases, cloud platforms and external data sources.

We help organisations establish reliable data models and semantic layers that provide consistent business definitions, relationships and metrics across reporting, analytics and AI applications.

Our AI Data Readiness Services

  • Data Warehouse Modernisation: Upgrade legacy environments to support modern analytical and AI workloads.
  • Semantic Layer Development: Establish reusable business definitions, measures and data relationships.
  • Data Integration: Consolidate structured and relevant unstructured data from enterprise systems.
  • Data Quality & Governance: Improve accuracy, consistency, lineage and access controls.
  • AI Data Preparation: Prepare trusted datasets for machine learning, predictive analytics and AI applications.
  • Analytics Integration: Connect enterprise data platforms with Power BI, Microsoft Fabric and other analytical technologies.

Whether you are developing predictive models, introducing AI-powered analytics or preparing enterprise data for generative AI applications, ExistBI can help establish the data foundation required for reliable results.

What does a Data Warehouse consultant do?

A data warehouse consultant takes the data scattered across your business and turns it into one reliable system your teams can act on. On a typical ExistBI engagement, that covers:

  • Data integration: connecting your CRM, ERP, Financial Data, Product Data, Social Media, e-commerce platforms, any stored Data through dependable pipelines
  • Data cleansing: fixing the missing fields, duplicates and format mismatches before they reach your reports
  • Data modeling: structuring the warehouse so queries stay fast at any data volume
  • Performance tuning: finding what slows reports down and removing it
  • Scalability planning: sizing the system for the data and users you expect over the coming years
  • Security and compliance: role-based access, encryption and audit trails from day one
  • Deployment, testing and training: taking the system live, proving the numbers match your source systems, and getting your team confident running it

The usual signs it is time to bring one in: teams argue over whose numbers are right, simple reports take days, a cloud migration is coming, or an AI initiative is underperforming because the data underneath is inconsistent.

Data Architecture: A Strong Foundation for Analytics

Good analytics start with a strong data foundation. Our data architecture consulting maps how data moves through your business, breaks up data silos, and designs clear pathways so information stays accurate from source to dashboard. We modernize legacy systems, run migrations into modern cloud platforms, and pair the warehouse with a data lake where large volumes of raw or unstructured data need a home. The result is one trusted place for every type of analytics, from daily reporting to machine learning.

Our Approach to Data Warehouse Consulting Services

  • Phase 1: Assessment, Strategy & Planning

  • We lay the foundations for a successful new Data Warehouse project:

    • We start with a Business Intelligence Assessment consisting of stakeholder workshops
    • Solidify stakeholders vision and objectives with both the business and technology team
    • Review Data Governance, Data Quality, Master Data Management, Data Warehouse and Reporting environments, existing systems, and Data Management strategy
    • Understand the current capability and scalability
    • Create a Risk Management Framework
  • Phase 2: Data Warehouse Analysis & Design

  • Our team analyzes your data sources, and translate detailed requirements into data structures that are scalable, resilient, extensible, and sustainable:

    • Review and document existing data sources and data connectors
    • Undertake analysis of existing reports, machine learning models, and data-mining needs
    • Conduct a gap Analysis on data sources
    • Conduct detailed analysis of Key Performance Indicators (KPIs) and Key data management processes
    • A Principal Consultant & Architect map out the logical design of the Data Warehouse
    • A Principal Consultant & Data Integration Specialist creates the logical design of the ETL architecture
  • Phase 3: Data Warehouse Build & Development

  • We build robust data warehouse, develop ETL processes for seamless data integration:

    • Physical design of databases and schemas
    • ETL routines development
    • Data profiling & testing bulk data (pre-load)
    • Loading of historical data into Data Warehouse
    • Data profiling & testing, including UAT
    • Data automation tuning
    • Data Warehouse Normalization
  • Phase 4: Data Warehouse Support

  • We provide ongoing support and maintenance for your data warehouse, including performance optimization, user training, and assistance with ongoing data governance for peace of mind:

    • Support will be provided per SLA request on all types of issues
    • Analysis of issue, urgency assigned and fixed per SLA
    • Provide custom support packages to suit your requirements
    • Helpdesk Ticketing Service (24×7)
    • Supervision of systems
    • Pro-active service options to avoid operational problems
    • Product support and fault elimination
    • Lowering storage and processing costs

How can your business benefit from Data Warehouse Consulting Services?

A well-designed enterprise data warehouse brings together information from across your organisation, creating a trusted foundation for business intelligence, analytics, reporting and AI. ExistBI helps organisations turn fragmented data into reliable, accessible information that supports better decisions and long-term growth.

  • Historical Insight

  • Bring years of business data together in one trusted environment to identify trends, patterns and changes over time. A data warehouse provides the historical perspective needed to better understand customer behaviour, sales performance, operational trends and other important business metrics.
  • Competitive Advantage

  • Make faster, better-informed decisions using consistent and reliable enterprise data. With trusted information available across the organisation, business leaders can evaluate market opportunities, customer behaviour, pricing, product performance and changing business conditions with greater confidence..
  • Increased Revenue And ROI

  • Turn enterprise data into actionable insight that helps identify new revenue opportunities, improve customer strategies and support better investment decisions. By making reliable information available across departments, a modern data warehouse can increase the value organisations receive from their data, analytics and technology investments.
  • Greater Operational Efficiency

  • Gain greater visibility into business processes, performance and resource utilisation. Integrated data makes it easier to identify bottlenecks, inefficiencies and emerging issues, helping teams improve processes, allocate resources more effectively and make decisions based on measurable business performance.
  • One Trusted Source of Business Data

  • Create a consistent foundation for reporting and analytics across finance, sales, marketing, operations and other business functions. By integrating data from multiple systems and applying common business definitions, a data warehouse helps reduce conflicting reports and gives decision-makers greater confidence in the information they use.
  • Ready for Advanced Analytics & AI

  • Establish the governed, high-quality data foundation required for advanced analytics, machine learning and AI initiatives. Modern data warehouses and semantic layers can provide AI and analytical applications with consistent business definitions, trusted measures and accessible enterprise data, helping organisations move from experimental AI projects toward scalable business solutions.

Why choose ExistBI for your Data Warehouse Consulting services?

  • Expertise & Experience

  • Our data warehouse specialist team has decades of experience providing Data Warehouse solutions. We assist clients with on-premise, hybrid or cloud data warehouse end-to-end projects.
  • Tailored Solutions

  • We offer customized data warehousing solutions to meet your business needs and industry requirements.
  • End-to-End Support

  • 300+ professionals across North America, the UK, and the European Union are ready to consult and support you throughout the entire data warehouse lifecycle, from strategy to ongoing maintenance.
  • Technology Agnostic

  • We work with leading data warehouse platforms and technologies to develop the most appropriate solution for your unique requirements.
  • Enhanced Data Security & Governance

  • We prioritize data security and ensure compliance with regulations.

Cloud Data Warehouse Consulting on Every Major Platform

Modern data warehouse environments increasingly combine cloud, hybrid and lakehouse architectures. ExistBI helps organisations evaluate, design, implement and optimise the right data platform based on their existing technology environment, workloads, performance requirements, scalability and budget.

Our cloud data warehouse consultants provide end-to-end support, from platform assessment and architecture through data migration, ETL/ELT development, implementation, testing, performance optimisation and ongoing support.

As a technology-agnostic consulting company, we work across leading cloud data warehouse and analytics platforms, including Microsoft Fabric, Azure, Snowflake, Amazon AWS, Google Cloud, Oracle, IBM and other enterprise technologies.

Microsoft Fabric & Azure Data Warehouse Consulting

ExistBI helps organisations design, implement and modernise Microsoft data warehouse environments using Microsoft Fabric, Azure Synapse Analytics, Azure SQL and related Azure data services.

Our Microsoft data warehouse services include architecture, cloud migration, data modelling, Fabric Data Factory and Azure Data Factory integration, semantic model development, Power BI integration, performance optimisation and ongoing support.

Our Microsoft data warehouse practice has delivered enterprise solutions across multiple industries, including a data warehouse implementation for a large US financial institution.

Explore Microsoft Data Warehouse Consulting →

Snowflake Data Warehouse Consulting

Our Snowflake consultants help organisations design, implement, migrate and optimise scalable cloud data warehouse environments. Services include Snowflake architecture and implementation, legacy data warehouse migration, ETL/ELT integration, data modelling, performance optimisation, security and integration with leading BI and analytics platforms.

We can also help organisations integrate Snowflake into broader cloud and multi-platform data architectures.

Explore Snowflake Consulting →

Amazon Redshift & AWS Data Warehouse Consulting

ExistBI provides Amazon Redshift and AWS data warehouse consulting for organisations building or modernising analytical environments on Amazon Web Services.

Our consultants support Redshift architecture, implementation, migration, data integration, workload optimisation and performance tuning, helping organisations build scalable AWS data platforms for reporting, analytics and advanced data workloads.

Explore Amazon Redshift Consulting →

Google BigQuery & Google Cloud Consulting

ExistBI helps organisations design and implement scalable analytical environments using Google BigQuery and Google Cloud data services.

Our consultants can assist with cloud architecture, data warehouse migration, data integration, modelling, performance optimisation and connecting BigQuery with business intelligence and analytics platforms.

Oracle Data Warehouse Consulting

Our Oracle consultants support organisations operating established Oracle data warehouse environments as well as those planning modernisation or cloud migration initiatives.

Services can include architecture, data integration, migration, performance optimisation and integration with modern BI, analytics and cloud platforms.

IBM Data Warehouse Consulting

ExistBI provides consulting for IBM enterprise data and analytics technologies, including data warehouse, data integration and related information management environments.

Our consultants can help organisations modernise existing IBM environments, integrate data across enterprise systems and connect IBM platforms with modern cloud, business intelligence and analytics technologies.

Cloud, Hybrid or Multi-Cloud — Choosing the Right Architecture

Not every organisation needs to move every workload to a single cloud platform. ExistBI evaluates your existing infrastructure, applications, data volumes, analytical requirements, security considerations and long-term technology strategy before recommending an architecture.

Whether your organisation is implementing a new cloud data warehouse, migrating a legacy platform, adopting a lakehouse architecture or integrating cloud and on-premise systems, we can help develop a practical roadmap and deliver the solution from architecture through implementation.

Not sure which data warehouse platform is right for your organisation?

FAQs

These services help you improve an existing data warehouse or build a new one from scratch, with solutions tailored to support your decision-making and strategy.

Since 2008, we have helped SMEs, large organizations, and Fortune 500 companies across 20+ industries, including healthcare, banking and finance, retail, manufacturing and supply chain, and Telecoms, consolidate disparate data into highly automated, scalable data warehouse and data lake solutions that enable timely, accurate analytics and streamline enterprise-wide decision-making.

We implement robust security protocols for encryption, restrict access control, and keep systems up-to-date to protect against viruses and hacking to safeguard your data.

Timelines vary based on numerous factors, with the most critical being:

  • Number of sources to be integrated into the Enterprise Data Warehouse(EDW)
  • Complexity of existing systems and their locations
  • On-premise, in the cloud or hybrid approach
  • Number of reports required
  • Number of subject areas
  • The volume of data to be migrated.

Typically, the initial phase, which includes identifying stakeholder goals, platforming, project road mapping, and implementation effort, takes between 5 and 20 days and is conducted as part of a data warehouse assessment (phase 1).

The project implementation phase itself can range from 3 to 9 months, depending on the scope. However, we are committed to ensuring efficient and timely implementations.

We conduct thorough assessments and collaborate closely to understand your unique requirements.

Whether you are looking to develop a new cloud, hybrid, or on-premise data warehouse or need to improve the performance of an existing one, our data warehouse consulting team will help you harness the power of your data and transform it into reliable, actionable intelligence that can drive business success!

Our pricing is tailored to your specific project requirements and budget. The exact figure, ranging from $20,000 to $2,000,000, will depend on DWH complexity and your expected deliverables. Please contact us for a free consultation to discuss your project in detail.

We have established policies and systems to ensure data security regulations, including GDPR, GLBA, US privacy laws (e.g., CCPA/CPRA), and PIPA. We conduct regular audits and update our security measures, policies, and procedures to ensure ongoing compliance.

Our obligation to your success continues even after implementation is completed. Our data warehouse consultants, along with our highly experienced strategy team, stand ready to address any issues, update software as required, and enhance your business as it evolves.

Yes, we budget for data warehouse hand-over training with full documentation to enable your team to operate, maintain, and support the data warehouse solution effectively. We also offer official, accredited, or fit-for-purpose technology training onsite or online to ensure your team is proficient in using all associated tools in the data warehouse project.

Our training programs have been utilized by government organizations, medium-large companies, as well as numerous Global 2000 and Fortune 500 companies.

We partner with you to define key performance indicators (KPIs) that are aligned with your strategic objectives. These KPIs could include:

  • Increased efficiency through faster data retrieval for analysis.
  • Improved decision-making based on precise and reliable data.
  • Enhanced operational performance through data-driven insights.
  • Increased user adoption and self-service analytics within your organization.

We track these KPIs throughout the data warehouse lifecycle and provide ongoing reporting to demonstrate the solution’s effectiveness and impact on your business goals.

Many teams try in-house first, and the pattern repeats: the build takes longer than planned, models designed for today buckle as data grows, and reports go live with numbers nobody fully trusts. Consultants have already made those mistakes on other projects and know where they hide. For most companies it is faster and cheaper to bring in specialists for the build, keep day-to-day ownership in-house, and take the training as part of the handover.

Look for delivered projects in your industry, platform independence (a firm tied to one vendor tends to recommend that vendor), senior consultants doing the work rather than only appearing in the sales conversation, and a fixed assessment phase that produces a clear roadmap before you commit to a full build. ExistBI has worked across more than 20 industries since 2008 and is platform agnostic by design.

Two ways. AI features are entering the platforms themselves: automated tuning, natural language queries, smarter pipeline monitoring. And AI projects raise the bar for the warehouse underneath, because model output is only as good as the data feeding it. A growing share of our engagements start as AI initiatives that stalled on inconsistent data.

ETL transforms data before loading it into the warehouse. ELT loads raw data first and transforms it inside the warehouse using the platform’s own processing power. Modern cloud platforms have made ELT the default for most new builds because it is faster to work with and keeps the raw data available. We build and optimize both.

    To discuss your project requirements, send us a message