We are one of the top data warehouse consulting companies building a modern data warehouse that turns scattered data into trusted, decision-ready insight. Our data warehouse consulting services help organisations design, implement, and optimise cloud and hybrid data warehouse platforms that support analytics, reporting, and operational decision-making at scale.
Whether you need to consolidate data from finance, Ecommerce, CRM, product, and marketing systems, or you’re modernising legacy reporting, our consultants deliver a warehouse foundation that is secure, cost-efficient, and built for long-term growth.
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Many organizations struggle with data silos, slow query performance, and high maintenance costs from legacy on-premise systems.
Our data warehouse consulting services bridge the gap between raw data and actionable business intelligence. We help you transition from “guessing” to “knowing” by implementing modern, cloud-native architectures tailored to your specific business KPIs.
We start with business outcomes and work backwards into architecture and design. You get a clear plan that aligns your data platform to your reporting needs, cost constraints, security requirements, and internal capability.
What we cover
Our Deliverables: target architecture diagram, source-to-target mapping, defined data domains and subject areas, plus a phased implementation roadmap.
We design and implement the warehouse, including ingestion, modelling, orchestration, and testing. If you’re migrating from a legacy warehouse or spreadsheet-based reporting, we run a controlled migration with minimal disruption.
Typical implementation activities
Most reporting pain comes from fragile pipelines, manual exports, and inconsistent refresh cycles. We build automated, auditable pipelines that keep your warehouse up to date reliably. Our scope include incremental loading strategies, change data capture patterns, schema evolution handling, data validation and reconciliation rules, plus error handling and alerting.
We integrate data from sources such as
We design analytical models that business teams can trust and understand, including conformed dimensions, fact tables, and business friendly naming.
Modeling deliverables include:
We establish governance that protects data integrity while improving usability for analysts and decision makers.
We implement:
We tune your warehouse for faster query response and better spend efficiency.
Optimization services include:
We support the full journey from strategy to execution: platform selection, architecture design, ingestion pipeline setup, data modelling zones (raw, curated, consumption), metadata and cataloging, security and access controls, and integration with BI tools. Whether you are starting from scratch or modernising a legacy environment, we build a roadmap that reduces risk and delivers value in phases.
Our Data Lakehouse Consulting service helps you combine the flexibility of a data lake with the reliability and query performance of a data warehouse so your teams can work from one trusted data foundation.
We design and implement end-to-end lakehouse architectures tailored to your environment, including ingestion, storage design, transformation layers, governance, and consumption for BI tools like Power BI and Tableau
A warehouse creates value when teams can use it quickly. We help your teams consume data through reliable dashboards and self service analytics.
Enablement includes:
If you want ongoing help, we provide managed support to keep pipelines healthy, add new sources, expand data marts, and continuously improve quality and performance.
Support options we offer:
Vidi Corp implemented a cloud-based data solution by establishing a robust relational database management system (RDBMS) connected via secure REST APIs and hosted on Microsoft Azure. This architecture enables real-time data flow from critical business systems into a centralized, scalable, and secure cloud environment. As a result we reduce manual data consolidation tasks across departments by 95% and data-entry errors by 80%. The team’s report generation time dropped from 48 hours to under five minutes.
Travis Kelley, CEO, War Room Operations
Vidi Corp helped us scrape 5M+ records from multiple websites. We then used this data to inform pricing decisions for products on our online marketplace. All milestones were forecasted clearly and achieved on time. The communication was second to none, even with changes I requested.
Louis Rooney, Commercial Director, Juno
We engaged Vidi Corp LTD to develop a custom-built API endpoint to automate our payroll processes. Our main objectives were to address issues with data duplication, overcome an API limitation of 1,200 requests, and reduce the total connector cycle time to ideally less than three hours. Their solution eliminated duplication, overcame API limits, and reduced cycle time. The team managed the project well, communicated effectively, and delivered on time throughout the engagement. Their creativity in addressing challenges really stood out.
Can Akbay, Strategy & Operations Lead, Integrity Landscape
We design your warehouse around the decisions that matter most to your business, not around technical preferences. At the start of every engagement, we align reporting priorities with leadership goals, operational KPIs, and team workflows. This ensures your data platform supports real decisions such as margin improvement, demand forecasting, customer retention, and cash flow visibility. The result is a warehouse that produces measurable impact, faster adoption, and clear return on investment.
Strong governance should increase trust without slowing delivery. We implement lightweight, effective controls across access management, data quality, lineage, and change tracking so your teams can move quickly with confidence. This includes role based permissions, clear ownership rules, quality checks at critical pipeline stages, and transparent audit trails. You get compliant, dependable data operations while still enabling analysts and business users to deliver insights at pace.
A warehouse is only valuable when people can use it easily. We model data specifically for analytics workloads so reports are fast, metrics are consistent, and self service is realistic. Our consultants structure datasets for common BI patterns, define reusable business metrics, and simplify complex source systems into clear, decision friendly models. This reduces report rework, avoids conflicting numbers across teams, and helps everyone work from the same trusted definitions.
Manual reporting creates delays and risk. We build resilient automated pipelines that keep your data current, accurate, and available when needed. Our approach includes orchestration, validation checks, retry logic, failure handling, alerting, and controlled backfills. Pipelines are designed to meet your operating cadence, whether hourly, daily, or near real time. You gain dependable refresh cycles, fewer disruptions, and a data platform your teams can rely on for day to day decisions.
Our consulting approach uses a structured, collaborative methodology that maximises delivery success while minimising disruption to day-to-day business operations.
Data Warehousing Consultation
We review your current data landscape, reporting requirements, existing pipelines, and pain points. We identify quick wins and define the warehouse scope.
Data Architecture and Implementation Plan
We design the target architecture and create an implementation roadmap that balances speed, governance, and cost.
Implementation and Integration
We implement ingestion, transformation, modelling, and orchestration. We validate data accuracy and deliver BI-ready datasets.
Dashboard Enablement and Handover
We enable BI tools such as Looker Studio, Power BI, Tableau, or Excel. We document everything and train your team.
Data Warehouse Experts Support
We provide continuous monitoring, performance optimisation, and expert support to keep your data warehouse efficient, reliable, and aligned with your changing business needs.
Data warehouse consulting is the professional service of designing, building, migrating, and optimising a data warehouse so organisations can consolidate data and produce reliable analytics, reporting, and AI-ready datasets.
A data warehouse is designed for structured analytics and reporting with curated, modelled datasets. A data lake stores large volumes of raw and semi-structured data. Many modern architectures blend both approaches (lakehouse) depending on requirements.
It depends on your cloud ecosystem, team capability, data volumes, governance requirements, and workload patterns. For example, BigQuery works well for Google Cloud stacks, while Snowflake supports cross-cloud flexibility. Azure teams may align with Synapse or Fabric
A focused warehouse with a small number of sources and a defined KPI scope can be delivered in a few weeks. Larger enterprise programmes with many sources, complex modelling, and governance needs can take multiple months. We typically deliver in phases so value appears early.
