Objective: Data & Analytics Proficiency

Status: Planning

Priority

P1
Category

Core
Target

Q3 2026

Why This Matters

Data work is everywhere in modern IT:

  • Security: Log analysis, threat hunting, SIEM queries

  • Networking: Traffic analysis, config audits, capacity planning

  • Cloud: Metrics, monitoring, cost optimization

  • Development: API responses, testing, debugging

  • Business: Reporting, automation, decision support

Building proficiency means:

  1. Scriptable workflows - Automate repetitive data tasks

  2. Cross-platform skills - Same concepts in bash, Python, PowerShell, JavaScript

  3. Tool fluency - JSON/YAML/CSV manipulation across environments

  4. Career expansion - Opens doors to data engineering, SRE, DevOps roles

Success Criteria

Criterion Description Met?

Regex fluency

Extract data patterns across all tools

[ ]

jq/yq mastery

Transform JSON/YAML fluently

[ ]

Python data work

pandas, json, csv modules for analysis

[ ]

Browser automation

JavaScript for data extraction

[ ]

Pipeline building

Chain tools together for complex workflows

[ ]

Documentation

Can teach these skills to others

[ ]

Current State

  • Regex: In progress (see Regex Mastery)

  • jq: Basic usage, need deeper mastery

  • Python: Can script, need pandas/data focus

  • JavaScript: Limited, need growth

  • Bash pipelines: Strong foundation

Skill Stack

Layer Tools Application

Pattern Matching

regex (BRE, ERE, PCRE)

Extract specific data from any text

Text Processing

awk, sed, cut, tr, sort, uniq

Transform and filter text streams

Structured Data

jq (JSON), yq (YAML), csvkit

Parse and manipulate structured formats

Programming

Python, JavaScript, Rust

Complex logic, APIs, automation

Storage

SQLite, PostgreSQL, files

Persist and query data

Visualization

matplotlib, D2, Grafana

Present insights

Action Plan

Phase Actions Target Status

1

Regex mastery (foundational)

Q2 2026

[ ]

2

jq/yq deep dive

Q2 2026

[ ]

3

Python data libraries (pandas, json)

Q3 2026

[ ]

4

JavaScript browser automation

Q3 2026

[ ]

5

Build portfolio of data scripts

Q3 2026

[ ]

Application Examples

Task Tools/Approach

Parse ISE logs for auth failures

grep -P + awk or Python

Extract IPs from firewall configs

regex + sed/awk pipeline

Query Kubernetes resources

kubectl + jq

Analyze email patterns

Python + Gmail API + regex

Search domus documentation

ripgrep + jq for structured output

Transform YAML configs

yq + shell scripts

Web scrape for research

JavaScript + browser console

Dependencies

Related Objectives