Tech Stack
| Need |
Tool |
| Quick exploration |
Jupyter, pandas |
| Heavy transform |
dbt, SQL, polars, DuckDB |
| Reporting |
Tableau, Metabase, Looker |
| Programming |
Python, SQL, R |
| Notebooks |
Jupyter, Hex, Mode, Observable |
| Version control |
Git, GitHub |
Spreadsheets vs. Databases
| Spreadsheets |
Databases |
| Software application |
Query language (SQL) |
| Rows and columns |
Rules and relationships |
| Cells |
Complex collections |
| Limited data |
Huge volumes |
| Manual entry |
Strict, consistent entry |
| Single user |
Multi-user |
| User-controlled |
DBMS-controlled |
SQL dialects
| Dialect |
Notes |
| PostgreSQL |
Open source, full standard, rich functions |
| MySQL |
Common; some quirks |
| SQL Server (T-SQL) |
Microsoft; uses TOP instead of LIMIT |
| BigQuery |
Standard SQL with array/struct extensions |
| Snowflake |
Cloud DW; ANSI SQL |
| DuckDB |
In-process OLAP; PostgreSQL-compatible |
| SQLite |
Embedded; minimal feature set |
Visualization comparison
| Tool |
Strength |
Cost |
| Tableau |
Polish, enterprise, ecosystem |
$$$ |
| Power BI |
Microsoft integration |
$$ |
| Looker / Studio |
Google integration; Studio is free |
Free–$$$ |
| Metabase |
OSS, easy SQL |
Free–$ |
| Mode |
Notebook + dashboard |
$$ |
| Hex |
Notebook + apps + AI |
$$ |
| Plotly |
Programmatic |
Free + paid Dash |
| Grafana |
Time-series, ops |
Free + paid |
Blockchain DA (specialized)
Data Management body of knowledge
For broader context: DAMA-DMBOK 2 — a foundational reference for data management practices.
References