Our Services

BI & Data Warehousing Services

Are you ready do to some really interesting things with your organizational data? BigDBoy can help you build and organize a data warehouse taking your internal systems and mapping those to business needs and concepts you care about, like customer trends, sales volume and marketing effectiveness. We can help you leverage volumes of data to gain new business perspectives to make better, faster decisions.

The Difference is Our Expertise

BigDBoy transforms your data into insights you can use your business for enhancement and service transformation.
Because we do it all: data strategy and planning, architecture, data warehouse implementation and maintenance; you work with one provider who gets to know your business and your data. Our knowledge and decades of experience in the entire data lifecycle goes into designing your well thought out business intelligence infrastructure maximizing the value of your data, leveraging existing assets and minimizing issues and additional costs down the road.
We build your data warehouse with a data science and analytics perspective, so it’s flexible should you decide later to add these more complex capabilities.


Our certified project managers are senior data and analytics practitioners who work with you to first identify requirements and dependencies. Then we oversee your project start to finish, managing milestones and deliverables to insure that your mission-critical project is completed on time and on budget.
We’ll help you articulate project requirements and determine success factors, then implement appropriate metrics and KPIs.
Traditional methods of reporting and dashboard development demand considerable time to define user requirements, build the tool, and put a useful product into users’ hands. Too often, the resulting product does not meet those user requirements, or the requirements have changed by the time the product is fully developed.


BigDBoy Data and Analytics Lifecycle Automation starts by helping you define your analytical needs from a business perspective. We combine our unique capabilities around the capture and management of data requirements with our rapid prototyping tool to automate your data and analytics lifecycle and put powerful analytic capabilities at your fingertips.
BigDBoy solves the problems inherent in traditional approaches to data and analytics lifecycle automation:


The right information architecture facilitates the use of data to further your corporate goals. Not only do we assess your current information architecture, we can transform it into a strategy-driven, enterprise-wide framework that powers pervasive business intelligence.
Our approach to information architecture encompasses your data architecture, data governance and master data management across business units, business functions, and technologies, utilizing a common vocabulary, and taxonomies for data organization and Master Data Management.
We combine objective, technology-neutral counsel with real-world business case experience to design an information architecture that unifies your data architectures under one core BI strategy that readily supports your business objectives.


In an information world, organizations that can harness large volumes of data for analysis have a distinct competitive advantage. Harnessing the exponential growth of data sources presents many challenges including shifting business priorities, budget concerns and long development cycles.
Data integration is at the heart of successful data and analytics projects. BigDBoy has a framework to determine if companies should take a traditional data integration approach or if data virtualization should be considered potentially providing an attractive cost-effective option.


Not every user has the time or expertise to sift through data to find answers. Others are visual thinkers for whom spreadsheets offer limited value. We transform numbers and percentages into visual depictions of important information that help business users manipulate dashboards, view information in context and identify data relationships and trends.