“You can’t start a fire without a spark.
— Bruce Springsteen
It seems trivial now, but I recall truly enjoying learning about relational data structures in “Introduction to Information Technology” during my business undergrad at the University of Washington. It was 1998 in Seattle, so Microsoft Excel (and Access) were center stage in our curriculum and this is where my spark began. I’m truly appreciative to those professors and TA’s I came across who made data both interesting and accessible.
My spark started to kindle a fire after graduation working as a Data and Financial Analyst at Andersen Consulting. It grew further as a Finance Manager at Microsoft, and years later leading me to work as a Technical Product Manager at company fanatical about data analysis and visualization – Tableau.
Through these years and roles, I’ve had direct experience with the following:
- Databases and associated query languages: SQL, SOQL, MySQL, PostgreSQL, MongoDB, Amazon DynamoDB
- Data transformation tooling and languages: Power Query, Tableau Prep, Python
- Data analysis and visualization: Power BI, Tableau Desktop, Pivot Tables, Pivot Charts
- End user interfaces: Power BI Embedded, Visual Basic for Applications (VBA), D3.js
- Ad-hoc and lightweight solutions: Smartsheet, Airtable, Postman
Leveraging this experience, Strand Consulting can help you:
- Understand your data and its potential
- Unlock and expose your data to more members of your team for greater impact
- Appropriately expose data to external customers and users
- Review your data needs and usage to recommend solutions and training
Please see my blog posts below for more about my fire for data analysis and visualization.
Using Power Query to Fetch Rain Data from the NOAA API
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.
Estimating Gallons Pumped from Sump Cycles
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!
Estimating Pump Cycles from Energy Consumption
Using my smart plug’s energy consumption measure, I estimate how often my sump pump runs.
Correlating Rainfall and Sump Pump Activity in Power BI
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?