---
title: Playbooks
url: http://0.0.0.0:4000/playbooks
content_type: landing
---

# Playbooks

How do I run a CluedIn project?
  Project leads, delivery teams and consultants.

Delivery methodology rather than product reference: how to scope a CluedIn project, sequence the work, and get to production. Playbooks link to the product documentation for the mechanics.

## In this section

- [Project delivery](http://0.0.0.0:4000/playbooks/project-delivery.md): How to scope and run a CluedIn project: what to decide before you start, how to sequence the work, and what has to be true before you go to production.
- [Data ingestion playbook](http://0.0.0.0:4000/playbooks/data-ingestion.md): How to decide what to ingest and in what order.
- [Data engineering playbook](http://0.0.0.0:4000/playbooks/data-engineering.md): Where CluedIn sits in a wider data architecture, and how far you should extend it before you should build around it.
- [Data transformation playbook](http://0.0.0.0:4000/playbooks/data-transformation-playbook.md) (how-to): Now that you have completed the data ingestion process and generated some golden records, it is time to start improving the quality of these records during data transformation.
- [Data export playbook](http://0.0.0.0:4000/playbooks/data-export-playbook.md) (how-to): Now that you have completed the data transformation process and reached the desired quality of your golden records, it is time to push golden records to the target systems in your organization.
- [Resources for Data Steward](http://0.0.0.0:4000/playbooks/resources-for-data-steward.md) (reference): This page includes links to relevant documentation and videos to help Data Stewards perform their tasks in the data quality virtuous cycle.
- [Go live in 14 days with CluedIn — step‑by‑step playbook](http://0.0.0.0:4000/playbooks/go-live-in-14-days.md) (how-to): This plan embraces ELT and iteration:
- [Implement CluedIn with AI](http://0.0.0.0:4000/playbooks/implement-cluedin-with-ai.md) (how-to): Ingestion → AI Mapping → Entities