Warren Lacaba

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BI Software Developer
Farmers Edge
June 2018 - Present

My job as a BI Software Developer with Farmers Edge is to make others' jobs easier. My main day to day tasks include writing Python scripts or creating Azure Data Factory pipelines to extract data, and then making and mainting Power BI reports using that data. Outside of my usual work, I'm also trusted to test out new tools and tech to see if they would help out team work better. Some examples of my work include:

Weather Forecast Emails

The purpose of this project was to take weather forecast data from the FarmCommand API and email that to customers. I did this by setting up a pipeline using Google Cloud Functions, Cloud Scheduler, and Pub/Sub. The first Cloud Function pulls in customer data, which includes contact info, a weather station ID to query, and preferred unit of measurement. This Function pushes each entry of customer data to a Pub/Sub topic. A second Cloud Function is triggered by the Pub/Sub topic. It queries the FarmCommand API to pull in weather forecast data, inserts that data into an HTML template, and then sends that out as an email through the SendGrid API. This pipeline sends 1000+ emails to customers daily.

Completeness Scripts

This project is for a multi-team effort to show how much of our data is properly filled in. I made a Cloud Function to match data from Microsoft CRM to data from the FarmCommand API and show how much is blank and whether there are discrepancies in the parts that are actually filled in. This function can be made to show different levels of granularity. I also made a Function to parse through Excel files stored on Sharepoint and calculate the percentages of data completeness for each given dimension.

Rep Commissions Report

This report is used to help calculate commission payouts we owe to our representatives. I'm primarily using Azure Data Factory to extract and transform data, but I've also made one Google Cloud Function to clean up an Excel file before reading it into the rest of the pipeline. There are many rules and exceptions to the calculations so I've had to remain very organized to keep track of all the changes made.

Monthly Acre Calculation Report

This report extracts data and shows contracts with the services associated with them, as well as the number of acres the customer has. I originally made the data extraction using Power BI Dataflows but have since then switched over to using Azure Data Factory. The report itself is built with Power BI. This report is quite important because it serves as a source of truth for further financial reports.

Improving Data Extractions

- I helped test Azure Data Factory as one of our main tools for data extractions. Many of the pipelines in this service used to be Power BI Dataflows, but our team found those slow and hard to document. Moving over to Azure Data Factory improved our work because it ran quicker, was able to be version controlled, and was more self-documenting due to the visual nature of the tool.

- Some parts of our CRM data weren't retrievable through the connection to Azure Data Factory, so I learned to use some of our existing Python code in Azure Functions. This allowed us to run Python code as a step in our Azure Data Factory pipelines.

- Since Farmers Edge has recently been moving to Google Cloud Platform, I've been learning about services like Google Cloud Functions and Pub/Sub and teaching them to the rest of the team. I've also been learning to extract data from BigQuery.

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