Executive Data Strategy Toolkit

$89

Board-ready data strategy deliverables: maturity assessment, ROI calculator, executive dashboards, vendor comparison, and First 100 Days plan.

📁 14 files🏷 v1.0.0

PythonSQLMarkdownJSONDatabricksRedis

📁 File Structure 14 files

executive-data-strategy-toolkit/ ├── README.md ├── assessment/ │ ├── maturity_assessment.md │ └── organizational_readiness.md ├── budget/ │ └── budget_request_template.md ├── business_case/ │ ├── business_case_template.md │ ├── roi_calculator.py │ └── vendor_comparison.md ├── dashboards/ │ └── executive_dashboard_designs.sql ├── metrics/ │ └── success_metrics_framework.md ├── reviews/ │ └── quarterly_strategy_review.md ├── roadmap/ │ ├── change_management_plan.md │ └── platform_roadmap_generator.md └── strategy/ ├── data_strategy_onepager.md └── first_100_days.md

📖 Documentation Preview README excerpt

Executive Data Strategy Toolkit

Product ID: executive-data-strategy-toolkit

Version: 1.0.0

Price: $89

Author: Datanest Digital (https://datanest.dev)

Category: Strategy

---

Overview

The Executive Data Strategy Toolkit is a comprehensive, ready-to-use collection of frameworks, templates, assessments, and tools designed for CDOs, Heads of Data, VPs of Analytics, and senior data leaders who need to build, communicate, and execute a modern data strategy.

Whether you're stepping into a new leadership role, preparing a board presentation, or building the business case for a data platform investment, this toolkit gives you production-tested templates and frameworks to move fast and lead with confidence.

What's Included

Assessment & Discovery

| File | Description |

|------|-------------|

| assessment/maturity_assessment.md | 80-question data platform maturity assessment across 8 dimensions |

| assessment/organizational_readiness.md | Organizational readiness assessment for data transformation initiatives |

Business Case & ROI

| File | Description |

|------|-------------|

| business_case/roi_calculator.py | Python ROI calculator with TCO comparison, payback period, and sensitivity analysis |

| business_case/business_case_template.md | Executive-ready business case template for data platform investment |

| business_case/vendor_comparison.md | Structured vendor comparison framework (Databricks, Snowflake, BigQuery, Fabric) |

Executive Dashboards

| File | Description |

|------|-------------|

| dashboards/executive_dashboard_designs.sql | 6 executive dashboard SQL designs for data platform KPIs |

Strategy & Leadership

| File | Description |

|------|-------------|

| strategy/data_strategy_onepager.md | Board/C-suite one-pager template for data strategy communication |

| strategy/first_100_days.md | First 100 days plan for new CDOs and Heads of Data |

Roadmap & Change Management

| File | Description |

|------|-------------|

| roadmap/platform_roadmap_generator.md | Platform investment roadmap template with phased delivery |

| roadmap/change_management_plan.md | Change management plan for data platform adoption |

Metrics & Governance

| File | Description |

|------|-------------|

| metrics/success_metrics_framework.md | Leading and lagging indicators framework for data strategy |

Reviews & Budget

| File | Description |

|------|-------------|

| reviews/quarterly_strategy_review.md | Quarterly data strategy review template |

| budget/budget_request_template.md | Budget request template with TCO breakdown |

Getting Started

... continues with setup instructions, usage examples, and more.

📄 Code Sample .py preview

business_case/roi_calculator.py #!/usr/bin/env python3 """ Data Platform ROI Calculator Executive Data Strategy Toolkit — Datanest Digital (https://datanest.dev) Calculates ROI, TCO comparison, NPV, and payback period for data platform investments. Supports scenario analysis and sensitivity testing. Usage: python roi_calculator.py # Interactive mode python roi_calculator.py --example # Run with example data python roi_calculator.py --json input.json # Load from JSON file Requires: Python 3.9+ (no external dependencies) """ from __future__ import annotations import argparse import json import math import sys from dataclasses import dataclass, field, asdict from typing import Optional @dataclass class CostItem: """A single line item in a cost model.""" name: str annual_cost: float category: str # "platform", "people", "tooling", "operations", "other" is_one_time: bool = False growth_rate: float = 0.0 # annual growth rate (e.g., 0.10 for 10%) notes: str = "" def cost_at_year(self, year: int) -> float: """Calculate cost for a given year (0-indexed).""" if self.is_one_time: return self.annual_cost if year == 0 else 0.0 return self.annual_cost * ((1 + self.growth_rate) ** year) @dataclass class BenefitItem: """A single benefit line item.""" name: str annual_value: float # ... 447 more lines ...

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