---
name: cost-optimizer-cloud-data-platforms-897854e52c6f
description: Analyzes and optimizes costs for cloud data platforms
version: 1.0.0
category: Cost Management
skillId: SK-DEA-012
allowed-tools:
  - Read
  - Write
  - Edit
  - Glob
  - Grep
  - Bash
graph:
  domains: [domain:data-engineering]
  specializations: [specialization:data-engineering-analytics]
  skillAreas: [skill-area:big-data-tools, skill-area:data-warehouse-modeling]
  roles: [role:data-engineer, role:analytics-engineer]
  workflows: [workflow:data-pipeline-deployment]
---

# Cost Optimizer (Cloud Data Platforms)

## Overview

Analyzes and optimizes costs for cloud data platforms. This skill provides deep expertise in platform-specific cost structures and optimization strategies.

## Capabilities

- Snowflake credit analysis and optimization
- BigQuery slot and on-demand optimization
- Redshift node sizing
- Storage cost optimization
- Query cost estimation
- Warehouse scheduling recommendations
- Data lifecycle policy recommendations
- Reserved capacity planning

## Input Schema

```json
{
  "platform": "snowflake|bigquery|redshift|databricks",
  "usageMetrics": "object",
  "billingData": "object",
  "queryHistory": "object"
}
```

## Output Schema

```json
{
  "currentCost": "number",
  "optimizedCost": "number",
  "savings": "percentage",
  "recommendations": [{
    "category": "string",
    "action": "string",
    "impact": "number",
    "effort": "low|medium|high"
  }]
}
```

## Target Processes

- Data Warehouse Setup
- Query Optimization
- Pipeline Migration

## Usage Guidelines

1. Provide platform-specific usage metrics
2. Include billing data for cost baseline
3. Share query history for optimization analysis
4. Prioritize recommendations by impact and effort

## Best Practices

- Regularly review and optimize warehouse sizes
- Implement auto-suspend and auto-resume policies
- Use clustering and partitioning to reduce scan costs
- Consider reserved capacity for predictable workloads
- Monitor and alert on cost anomalies


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Marketing, Product Management, Sales
Roles: Business Development, Data Analyst, Data Scientist, Growth Marketer, Product Manager
Specialties: API
Tools: Bigquery, Databricks, Redshift, Snowflake
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: fa42fb7ed400a1237cf66826eb2f9ba24df7f5ccb82c274061dee61abbadcf8d