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Representative Project Experience

Built dashboards and a data mart that integrated public data sets, purchased data and customer data to predict jet fuel purchasing patterns nation-wide in near real-time.

Created a predictive model in R that promised a 9% increase in sales for a multi-location retailer by optimizing staffing.

Recruited, hired and managed dozens of analytics professionals. Worked with clients to develop staffing plans and recruiting efforts for analytics.

Led the creation of a crawler to extract millions of prices from competitors web sites and match their products to those of our client to drive quick reaction to price changes.

Facilitated Business Event Analysis and Modeling (BEAM) design sessions that allowed a large regional health care practice to assess the consistency of their prenatal care delivery.

Built time-series based exploratory models in R to assess retail promotions effectiveness.

Created a sales data mart to analyze channel performance for a major financial investment products firm.

Applied Monte Carlo techniques to multi-variate optimization problems in healthcare delivery.

Implemented enterprise Business Intelligence (BI) applications with over twenty clients in finance, food, forest products,catalog retail, insurance and trucking companies.

Designed and led the development of an application to calculate customer profitability across multiple divisions and product lines for a regional bank.

Developed communication plans to help organizations encourage the use and understanding of data.

Technology Experience

Relational Databases - Over twenty-five years experience designing and creating relational databases. Most of that experience is with Azure SQL and Microsoft SQL Server with additional project experience in Oracle, DB2 and Progress.

Structured Query Language (SQL) - Extensive experience in Transact-SQL and ANSI SQL along with some PL-SQL experience. Both data definition and querying. Teaching of advanced SQL to analysts. The last several years have been primarily in Azure SQL Database.

Source control with Git and TFVC - Many years experience with Git and the automation of data warehouses, ETL code and other artifacts using automated builds.

Extraction, Transformation and Loading (ETL) - Over twenty years experience in loading and transforming data with Azure Data Factory and SQL Server Integration Services (SSIS). Many projects with a wide range of data sources from Comma Separated Value (CSV) flat files to JSON, website scraping, relational databases, COBOL file stores, ISAM, etc. We've integrated data from Dynamics, Navision, Epicor and many other business apps.

Programming languages - over twenty years of heavy software development experience. Focused on C#, Javascript and Powershell recently. Over eight years experience in statistical analysis and forecasting time series with R and RStudio.

Cloud services - Working with the Azure cloud services since 2014. Services used include: Azure SQL Database, virtual machines, Azure Functions (serverless), Webjobs, storage accounts, Key Vault, Azure Automation, App services and API Management. Experience in automated deployments and infrastructure as code using Bicep, Powershell and ARM templates.

Enterprise reporting - Many years with Power BI. Some of the early years were painful! Worked with the Power BI REST API and XMLA endpoint for automation and observability. Additional experience with Cognos, Business Objects, Tableau and Crystal.

Frameworks - experience in building web applications with Bootstrap and Angular.

Test Automation - recent heavy experience with Selenium as well as Microsoft Visual Studio Test and SQL Server Data Tools (SSDT) unit testing. We've also built custom frameworks for regression testing of data and ongoing data quality assessment.

Web development - Application and website development using C#, Javascript, ASP(x) and WebForms. Many years experience in debugging web applications using Fiddler, Chrome Dev Tools and others.

Continuous Integration (CI) - we primarily use the CI features of Azure DevOps to automate builds, testing and releases to multiple environments such as Dev, Test and Production.

Dimensional Modeling - using the Kimball dimensional modeling techniques including slowly changing dimensions, snapshots and other techniques to make data more accessible for reporting and analysis.