-
Demark Indicators Analysis
Demark Indicators are signals use to predict big trend reversals (buy the dip or sell the rip). The pattern is a very counterintuitive, you can read more here. An interesting person had to have come up with this. In any case, I was interested in this because of how strange it is. Also, as far…
-
What we talk about when we talk about AI
Marshal McLuhan said something along the lines of people prefer to hear bad news because there’s always bad news and they know how to react to that. Say that’s too bad and move on. But when people hear good news they get uncomfortable because good news means change and people don’t know how to feel…
-
Building a Data Lake on AWS
Never Miss an Update! I kinda wandered into data engineering on accident. When I was a good little data analyst, I would spend some of my time optimizing queries and building automating reporting process. I learned more about how SQL databases work: that having a ton of joins slows queries down, why normalization exists for…
-
Custom Maps with Python
If you’re anything like me, a strategy gamer. You’ve spent way too many hours staring at this view of the Mediterranean. A good map should draw you in. I’m going to give you a quick guide in making one using Python. Github Link The code to make maps is relatively simple thanks to the matplotlib…
-
World War II in the Pacific Visualized
The Story this tells The Importance of Oil Roger said it best. Japan needed oil to fuel their war in China. The decisions to invade Indonesia and attack America were because of oil. and Japan’s ultimate defeat was a result of their industrial capacity grinding to a halt. The Navy and Submarines Amateurs talk about…
-
Webscraping in 15 Minutes
Data Science in a business context, is about leveraging Computing, Statistics, and expert domain knowledge together to solve problems and get results. Using the right tool for the job is where computing comes into play. Process improvement and Automation is the easiest way to create value with Data Science skills especially if you are starting…
-
Taking your SQL to the Next Level
Often when people learn SQL on the job or in school the being with writing queries, doing joins and maybe some update statements. This post is for those that are trying to move to the next level. This post will touch on the concepts data modeling, data normalization, Connecting to a SQL Database with Python,…
-
Rumblings in the labor market
I am going to make a case for some real actual inflation, the kind that stocks don’t like. I’m not going to mention any of the usual inflationista the Federal Reserve Balance Sheet, Money Printing, or even Supply Chains. Yes, a truly hot take. The inflation that I see as a underappreciated risk is labor…
-
KUNG I-CHI
You probably know a Kung I-chi in your life. A “gifted kid” that never amounted to much (and still mentions it), a liberal arts major who is underemployed, and/or a recent graduate who has significant student debt.
-
Mastering Data Engineering: Key Concepts, Tools, and Best Practices
I’m going to tackle a question I get all the time: “What is data engineering?” Many people wonder why it’s important, why we need it, and what it actually involves. In this post, I’ll answer these questions and delve into some key concepts and common tools used by data engineers. Understanding Data Engineering Data engineering…
-
R vs Python in Data Work: A Comprehensive Comparison
Today, I want to dive into a topic that often sparks lively debates in the data community: the comparison between R and Python for data work. Both languages have their distinct strengths and are valuable tools in a data professional’s arsenal. Having used both in various production contexts, I’ve seen firsthand how each can shine…
-
Simplify Data Ingestion from HubSpot to BigQuery with DLT Hub and Dagster
I want to dive into an exciting project I recently completed using DLT Hub, a Python library designed to simplify data ingestion and replication. In this project, I built a straightforward data ingestion pipeline that transfers data from HubSpot to BigQuery, leveraging the power of both DLT Hub and Dagster. This project turned out to…
-
Python Data Orchestration Project: Leveraging Dagster for Spotify Ads Integration
This content explores the integration of a data pipeline into a data warehouse using the Python-based orchestration tool, Dagster. It covers the significance of data orchestration, the role of Dagster in the project, and the project’s overview, including the data source, schema, and update frequency. The post details the components of the project structure and…
-
Video – Financial Conditions Index with Python
I was feeling idle and decided to brush up on my economics analysis skills as one does. Being a fan of the big short, I share that fantasy of seeing a pattern in the data that can give you an edge in financial markets. The Federal Reserve is always putting out cool research and easily…
-
Video – Basic Marketing Analytics with Python
I decided to start making video content. For this one I go over an example project of marketing data and guide you through some simple analysis. Github Repo can be found here.
-
Data Ingestion With REST APIs (LinkedIn Ads Example)
The Bezos API mandate In the Jeff Bezos mandate referenced in the iconic Steve Yagge platform rant, he talks about how Amazon implemented the service interface platform that grew into AWS. Using REST APIs for applications has a lot of benefits such as flexibility, scalability, security, and interoperability. Analytics use cases have different needs than…
-
The Golden Age of the Business Process Analyst
In large organizations and in legacy industries you’ll find these roles for business process analysts. A lot of admin work ultimately boils down from moving data from system A to system B and applying some transformation along the way. Is this just ETL? At a high level yes. The Data Science bubble of the 2010s…
-
Dagster with Spotify Ads API
I work at a marketing agency and reporting from janky marketing tools can be quite the challenge . Spotify Ads is one of those sources that previously required manual csv exports and formatting to report to the client. This process sucked up time that could be spent providing analysis or other higher level value add…
-
Subscribe
Subscribed
Already have a WordPress.com account? Log in now.
He Was A Data Boi 