A Second-brain for SQL

PARA method

// For visual thinker, you might love this:

Here's our ultimate productivity system for organizing SQL queries, we've put it all into one canvas. Visit this link to explore organization ideas.


With AI generating more SQL queries, we increasingly need tools to manage and keep track of these AI-generated SQL and metadata.

People can now generate more queries/views/tables but no one is organizing them properly.

This is why we are focusing on designing a space for your SQL scripts and keeping your queries/views/DDLs in order.

Example structure

Credit: workflowy

1. Projects

Specific SQL projects you're working on

  • alignment with goals and objectives

  • easier collaboration

  • streamlined workflow

When working on a project, you often need to execute a series of queries in a specific order. Organizing by project keeps these sequences intact and easily accessible.

2. Areas

Long-term responsibilities you want to manage over time.

  • consistent focus

  • routine tasks

  • long-term relevance

Organizing queries by ongoing business areas aids in routine tasks. It ensures you're not recreating or searching for the same queries on regular analyses.

3. Resources

A topics or interests that may be useful in the future.

  • Documentation on SQL syntax

  • Consistency across analyses

  • General-purpose or template queries

It's useful for referencing standard analysis patterns.

4. Archives

Archive SQL snippets, code examples, and solutions you encounter

  • Troubleshooting steps

  • Change tracking

  • Archived queries serve as a historical record

By moving older, less frequently used queries to an Archives section, you keep your active working areas uncluttered and focused on current tasks. This makes finding relevant, up-to-date queries faster and easier.

3 digits approach

Top level categories are

- 0 EDA
- 1 Insights
- 2 Advanced analysis
- 8 Resources
- 9 Archive

Example structure

000 - EDA

Getting to know the data by identifying patterns, understanding data distribution, and checking assumptions.

0xx - EDA
- 000 How many unique Xs are in the dataset?
- 002 What is the distribution of X across Y?
- 003 What is the time range of the dataset?
- 004 Are there any missing/inconsistent data points?

100 - Insights

Tie data observations to business-relevant questions

1xx - Insights
- 100 which products are seasonal?
- 101 What is the correlation between marketing spend & sales volume?
- 102 How do sales vary across different customer segments
- 103 ...

200 - Advanced analysis

Involves applying statistical or ML methods for segmentation, prediction, etc.

2xx Advanced analysis 
- 200 RFM analysis
  - 201 Segmentations
  - 202 ...
- 210 Churn analysis
- 220 Sales forecasting
- 230 Market basket analysis

Structured analysis approach

Categorizing your data analyses into different levels can help structure your approach and derive actionable insights.Categorizing your data analyses into different levels can help structure your approach and derive actionable insights.

Here's how you might categorize data questions into EDA, Insights, and Advanced Analysis:

  1. EDA (Facts): Establishes a foundation by understanding the data's basic characteristics.

  2. Insights: Begins to tie data analyses to business-relevant questions.

  3. Advanced Analysis: Focuses on applying statistical methods and models to drive decision-making. Often where the most value is extracted from data.

4 Levels of Data analytics

  1. Descriptive Analysis: Focuses on describing the current state of affairs and answering "what happened?" Uses basic metrics and data visualization.

  2. Diagnostic Analysis: Seeks to answer "why did it happen?" Involves more in-depth exploration of data to understand causes and relationships.

  3. Predictive Analysis: Tries to forecast future outcomes, answering "what could happen?" Utilizes statistical models and machine learning.

  4. Prescriptive Analysis: Answers "what should we do about it?" Involves using insights from all previous stages to inform decision-making and strategy.

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