Concepts in Data Science & Analytics, page 8
Dashboard Design: Guide, Don't Overwhelm
A good dashboard guides users to an insight, not just displays charts. Place your key takeaway in the top-left and limit views to 2-3 to maintain focus. The biggest mistake is including too many views, which clutters the message and slows down the dashboard.
Data Sonification: Hearing Your Data's Story
Data sonification is data visualization for your ears, mapping data points to sound properties like pitch or volume. It helps find patterns in complex datasets, like network traffic, where visuals fail.
How a SQL SELECT Query Actually Runs
A SQL SELECT query runs in a different order than you write it. It first builds the dataset with FROM/JOINs and filters it with WHERE, only then computing the final columns in SELECT. This is crucial for debugging.
The Big Idea: Your Presentation's Single-Sentence Core
The "Big Idea" is a single sentence distilling your presentation's core message. It must state your point of view and what's at stake, telling your audience what to know and what to do.
Python Virtual Environments
A virtual environment is an isolated Python installation with its own packages, so each project gets the exact dependency versions it needs without conflicting with other projects or the system Python.
Vectorization: Ditch the Python Loop
Vectorization means issuing one batch command to C-backed arrays instead of looping in Python. Use it for million-row DataFrames or matrix math. The footgun is treating apply() as vectorized, or silently materializing giant temporaries that exhaust RAM.
Spark Structured Streaming: Unify Batch and Stream
Spark Structured Streaming treats a live stream as an unbounded DataFrame. It unifies batch and streaming ETL on Kafka, but the footgun is confusing event time with processing time without watermarks, which silently drops late data.
ML Model Registry: Source of Truth for Production Models
A model registry is version control for trained models, not just code. It tracks which artifact is running in production, who approved it, and how it was built. Skip it and you get untracked files in S3 with no way to reproduce a production model.
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