Data Warehouse Consulting Services

Since 2008, ExistBI has helped hundreds of organizations get their data right. Previous customers include NASA, Pfizer, Nike, Costco, Sony, US Bank, Johns Hopkins and Northrop Grumman. We work from offices in Los Angeles, Jersey City, Washington DC, London, Berlin, Denver, Cleveland and Zagreb.

We are platform and tool agnostic. Whether your warehouse should run on Snowflake, Microsoft Fabric, Azure Synapse, Amazon Redshift, Google BigQuery, IBM Db2, Cloudera or on-premise SQL Server, we design the solution around your data and your goals, not around a vendor.

Most teams bring us in when reports take days, departments disagree over the numbers, or a cloud or AI initiative exposes weaknesses in the data underneath.

Since 2008 · 300+ consultants across North America, the UK and the EU · 20+ industries · SMEs to Fortune 500

from data warehouse to real time data streaming

Data Warehouse Consulting & Implementation Case Studies

Recent data warehouse projects, delivered end to end:

Process Insights – Complex Cross-Border Cloud Data Warehouse with Azure SQL and Power BI Case Study

Recent Case Studies, BI Analytics Case Studies, Business Intelligence Case Studies, CRM Case Studies, Data Integration Case Studies, Data Lake Case Studies, Data Quality Case Studies, Data Science Case Studies, Data Warehouse Case Studies, ERP Case Studies, Industry: Manufacturing, Industry: Retail, Machine Learning Case Studies, Microsoft Azure Case Studies, Microsoft Case Studies, Microsoft Power BI Case Studies, Predictive Analytics Case Studies, Regulatory Compliance Case Studies, Salesforce Case Studies, Support Services Case Studies

Read how ExistBI designed a tailored solution that will give unprecedented insights into the company’s operations across international locations.

Boyd – Data warehouse delivers unified view and decision-making

Data Warehouse Case Studies, BI Analytics Case Studies, Big Data Case Studies, Business Intelligence Case Studies, CRM Case Studies, Data Governance Case Studies, Data Integration Case Studies, Data Lake Case Studies, Data Migration Case Studies, Data Quality Case Studies, Data Science Case Studies, ERP Case Studies, Industry: Manufacturing, Informatica Case Studies, Machine Learning Case Studies, MDM Case Studies, Microsoft Azure Case Studies, Microsoft Case Studies, Microsoft Power BI Case Studies, Predictive Analytics Case Studies, Recent Case Studies, Regulatory Compliance Case Studies, Salesforce Case Studies, Support Services Case Studies, Tableau Case Studies

Learn how ExistBI designed a data warehouse using MS SQL Server, Informatica and Power BI for complete view of global operations.

Brookshire Brothers – Data Warehouse Consulting and Analytics for retailer

Recent Case Studies, BI Analytics Case Studies, Business Intelligence Case Studies, CRM Case Studies, Data Integration Case Studies, Data Quality Case Studies, Data Warehouse Case Studies, ERP Case Studies, Industry: Retail, Microsoft Azure Case Studies, Microsoft Case Studies, Microsoft Power BI Case Studies

Learn how ExistBI crafted a data warehouse and analytical platform so the supermarket chain could improve efficiency, and decision-making.

Our Data Warehouse Consulting Services

Data Warehouse Strategy & Design
Our principal consultants define your analytics needs and KPIs, design the right enterprise data warehouse or data lake model, and hand you a build plan that scales as the business grows.

Data Integration & ETL / ELT Services
We build and optimize the pipelines that move data from your CRM, ERP and applications into the warehouse. That covers new ETL or ELT builds, repairing slow or failing pipelines, and real-time feeds where the business needs them.

Data Modeling Service
We design the data structures your reports and dashboards sit on, so queries stay fast as data volumes and user counts grow.

Data Governance & Data Quality Management
We set up the policies, controls and checks that keep your data accurate, consistent and compliant, so every team works from numbers it can trust.

Data Security & Compliance
We implement access controls, encryption and audit trails in line with GDPR, CCPA, HIPAA and industry regulations, across cloud, hybrid and on-premise environments.

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 and applications 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?

Historical Insight
Accurate history in one place surfaces customer trends and behavior you can act on.

Competitive Advantage
Decisions on pricing, product and market moves rest on current, reliable data.

Revenue And ROI
Better insight in every department compounds into measurably better judgment calls.

Operational Efficiency
Bottlenecks become visible, and resource decisions follow the data.

One Source Of Truth
Finance, sales, operations and marketing work from the same numbers, updated in real time. Every division feeds the same standard, so analytics stay dependable as you grow.

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

Most of our current projects are cloud or hybrid. We help you choose the right platform for your workloads and budget, design the architecture, and run the migration. For Microsoft-centered teams, our Microsoft data warehouse practice covers Azure Synapse, Azure SQL and Fabric end to end, including the build we delivered for a large US bank (case study). On AWS, our Amazon Redshift team handles new builds and tuning.

Microsoft Fabric Data Warehouse	Google Big Query Cloud Data Warehouse	Oracle Data Warehouse
Microsoft Azure Synapse / SQL Data Warehouse	AWS Amazon Redshift Cloud Data Warehouse	Snowflake Data Warehouse
SAP Data Warehouse Cloud	Cloudera Data Warehouse	IBM Cloud Warehouse

Get a full list of our technology expertise

FAQs

How can data warehouse consulting services benefit my organization?

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.

What industries do you specialize in for data warehouse consulting?

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.

How do you guarantee the security and confidentiality of data within a warehouse?

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.

What is the timeline for implementing a data warehouse solution?

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.

How do you assess our organization’s data needs and tailor solutions accordingly?

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!

What is your pricing and cost structure?

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.

How do you ensure data security and compliance with regulations during implementation?

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.

What ongoing support and maintenance services do you offer after the implementation?

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.

Can we expect comprehensive training for our team members regarding the operation and maintenance of the data warehouse?

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.

How do you measure the success and effectiveness of your data warehouse solutions?

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.

Why hire a data warehouse consultant instead of building in-house?

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.

How do I choose among data warehouse consulting companies?

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.

How is AI changing data warehouse consulting?

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.

What is the difference between ETL and ELT?

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.