"You can't start a fire without a spark." – Bruce Springsteen
My journey into data analysis began with relational data structures studied during my business degree at the University of Washington in 1998. I worked progressively through roles including:
SQL, SOQL, MySQL, PostgreSQL, MongoDB, Amazon DynamoDB
Power Query, Tableau Prep, Python
Power BI, Tableau Desktop, Pivot Tables, Pivot Charts
Power BI Embedded, Visual Basic for Applications (VBA), D3.js, Smartsheet, Airtable, Postman
Strand Consulting can assist with understanding data potential, expanding team data access, exposing data to external customers, and reviewing data needs to recommend solutions.
In this post, I will explain how to use Power Query within Power BI to fetch daily rainfall data from a NOAA API and transform this data prior to presentation in a visualizations. Don't let the image fool you, no coding required. It's just too easy.
In my previous post, I derive how often my sump pump was firing. Here I estimate how much rainwater is getting moved out each time my pump cycles. It's got geometry!
Using my smart plug's energy consumption measure, I estimate how often my sump pump runs.
When my basement flooded during heavy Oregon rains, it rattled my cage. Being data oriented, I asked myself how how much rain was necessary to cause my sump pump to expel water?