Turning Raw Data into Clear Decisions 

Quickbook Finance Dashboard

Designed and implemented an end-to-end BI solution for financial reporting:

• Data Integration: Extracted raw financial data from QuickBooks using Python and loaded it into Azure SQL.

• Data Modeling: Performed transformations and built a star schema in Azure SQL to optimize query performance.

• Reporting & Analytics: Connected Power BI to Azure SQL views to create executive dashboards with dynamic time intelligence (Selected Month, QTD, YTD) and benchmark comparisons against Last Year, Last Month, and Budget.

• AI-Powered Insights: Integrated OpenAI via Python to generate automated narrative insights from financial data, providing executives with actionable commentary alongside visual analytics.

Sales Analysis Dashboard

Rora Orchards Sales Analysis Dashboard

This Power BI solution delivers end-to-end sales and payment visibility for Rora Orchards across its fruit and blueberry operations, covering both consignment and bin-based sales channels.

Data Architecture

Sales data is sourced from an on-premises SQL Server database, connected to Power BI and refreshed via an On-Premises Data Gateway . Payment data follows a separate automated pipeline: payment files are received by email, triggering a Power Automate flow that detects incoming attachments, extracts the files, and saves them to SharePoint. Power BI then connects to both SharePoint and SQL Server to consolidate sales and payment data into a unified reporting layer.

Dashboards & KPIs

The solution includes four report pages:

• Consignment Dashboard — tracks STD Cartons Sold , Total Payment, KG Sold , R/Carton , and R/KG , with paid vs. not-paid breakdowns and trend lines across the season.

• Bins Dashboard — monitors #Bins Sold , Total Payment , Tons Sold , R/Bin , and R/Ton , segmented by agent, farm, commodity, variety, and packing method.

• Sales Detail Table — a flexible drill-through view showing STD Cartons and R/KG by commodity and variety, with a dynamic dimension selector allowing users to pivot the breakdown by Agent, Farm, Commodity, Variety, Export/Local, or Size — and a measure selector to switch between multiple KPIs simultaneously.

• Future Payments Analysis — Outstanding payments totaling, broken down by commodity and agent, with ablity to see payment by week,month and year.

All dashboards include slicers for Season, Agent, Farm, Commodity, Variety, and Export/Local class, enabling users to dynamically filter every visual and KPI.

Rora Orchards Berries Picking Dashboard

This Power BI solution provides end-to-end operational visibility into the blueberry picking season, covering productivity, quality, wages, and environmental conditions across multiple farms and varieties.

Data Architecture

Picking data is sourced from an on-premises SQL Server database connected via an On-Premises Data Gateway. Budget data is maintained in Excel files stored on SharePoint, which Power BI connects to directly for seamless actual-vs-budget comparisons. Weather data is pulled live via an external API, enabling correlation analysis between environmental conditions and berry quality metrics.

Dashboards & KPIs

The solution includes five report pages:

• Picking Analysis — tracks Hectares Planted, Picking KG (Actual vs Budget), Picking Wages (Actual vs Budget), and Picking R/KG across farms, varieties, grades, and orchards. Budget variance indicators show performance above or below target at a glance, with breakdowns by grade (Class 1, Waste, Frozen) and variety.

• Picking vs Consignment Analysis — bridges operational and commercial data by comparing Picking KG against Consignment KG per variety, with weekly/monthly trend views and a consignment class breakdown (Export, Local, Frozen, Juice). Variance indicators immediately flag where picking volume isn't converting to consignment as expected.

• Picking Wages Analysis — a smart narrative summary auto-generates key highlights including peak wage weeks, highest picking hours, average weekly wages, and average R/Hour. Wages are broken down by type (Contractor vs Employees) and by company, with a full weekly trend across the season.

• Sizeband Analysis — monitors berry size distribution across six size bands (under 12mm through 20mm+), with Average Weight and Average Durafel score per variety. Views switch between daily and monthly trends, and a variety tab bar allows quick comparison across all blueberry cultivars.

• Durafel & Weather Analysis — correlates berry firmness (Durafel score) and average berry weight against live weather data including Max/Min Temperature and Rainfall. The Durafel vs Standard Deviation chart highlights consistency and quality risk periods, while the daily detail table layers all metrics for precise operational review.

All dashboards include slicers for Season, Farm, Variety, Orchard, Grade, and Month, giving users full control over the scope of analysis across every page.

HR Headcount Dashboard

HR Talent Acquisition Dashboard

HR Service Request Dashboard

Procurement Summary Dashboard

Financial Analysis Dashboard