---
title: "Who Deliver the Data and Tooling to Meet the Strategy"
slug: "who-deliver-the-data-and-tooling-to-meet-the-strategy"
description: "Test Data at the Enterprise series from Curiosity Software. Who Deliver the Data and Tooling to Meet the Strategy for a better test data strategy."
tags: ["Test Data Strategy", "Learning Portal", "Test Data Automation"]
updated: 2023-01-27T11:35:24Z
published: 2023-01-27T11:35:24Z
---

> ## Documentation Index
> Fetch the complete documentation index at: https://knowledge.curiositysoftware.ie/llms.txt
> Use this file to discover all available pages before exploring further.

# Who Delivers the Data and Tooling to Meet the Strategy

## Who Delivers the Data

- **Who Delivers the Data:**many delays in testing are down to testers waiting for data to be delivered to them.

Rich Jordan, suggests that assembling a test data team and thus centralising your organisation’s test data capability will gain you time and avoid dev teams waiting around for data requests to be fulfilled.

Beyond this time saving benefit, a centralised test data capability helps to standardise around common attributes, like getting PII anonymised.

The ultimate ask though falls on economies of scale, ie, does each team need its own data capability or is it better on time and cost to source that data from a single dedicated team?

[Embedded content](https://www.youtube.com/embed/Lqg999pwcl0?&wmode=opaque&rel=0)

---

## Tooling to Meet the Strategy

- **Tooling to Meet the Strategy:**too many organisations rely on rudimental tools and techniques to create test data.

Rich Jordan, proposes that tooling alone isn’t enough, and that a good Test Data Strategy also addresses the range of capabilities and complexity of expertise the tooling adds to an organisation.

At entry level, do you understand where PII exists (profiling), where technical debt is in the system (comparison), and which data needs anonymising (masking)?

More fully, what’s the size and shape of your data (synthetic data gen), the pace and efficiency (subsetting to shrink data volumes) of usage?

Or for an ephemeral environment strategy around DevOps (virtualisation) how do these all inform strategic decisions about tooling?

Ask yourself, do you have the requisite tooling that helps you understand and resolve the problems you are facing when it comes to test data?

[Embedded content](https://www.youtube.com/embed/_vFvpdZgbT4?&wmode=opaque&rel=0)

## Related

- [Test Data Strategy at The Enterprise](/test-data-strategy-at-the-enterprise.md)
- [Data Regulation, Architecture and Technology](/data-regulation-architecture-and-technology.md)
- [Delivery Methodology and Organisation Debt](/delivery-methodology-and-organisation-debt.md)