DataSF Guides: How to Ensure Quality Data
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DataSF Guides: How to Ensure Quality Data
Introduction
Data Lifecycle
Roles and Responsibilities
How To: Plan and Define Phase
Appendix: Data Quality Metrics
Appendix: Acknowledgments
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Introduction
We designed this DataSF guide to help you ensure quality data for services and programs in the City and County of San Francisco.

What is data quality?

There are lots of ways of measuring data quality. A quick definition is: the degree to which you can trust the data you are using for the purpose at hand.

What is the purpose of this guide?

To improve the quality of City data by providing a standard way to plan for and manage quality through the data lifecycle.

Why does data quality matter?

Because problems with data quality can:
  • Lead to inaccurate decisions or conclusions
  • Increase costs (staff time, confusion, repetitive questions and issues)
  • Create compliance or legal risk

How can I use this guide?

You can use this guide as a method or checklist to plan for and obtain new data. If you already have data, we will be developing another guidebook on improving data quality.
Use our companion worksheet to help you work through the guide.

Who should use this guide?

Anyone affected by or responsible for obtaining, managing or using data for a program or service in the City. This includes:
  • The program or service owner, manager or executive
  • Program staff
  • Business analysts
  • IT staff, including developers and database managers
  • End users of the data
Read Roles and Responsibilities for more detail.

What background do I need for this guide?

We designed this guide for a large span of backgrounds. For some of you, this information will be brand new. Others may already be experts and can skip any familiar sections. Part of our goal is to develop a shared set of practices and approaches regardless of background.

How can I provide feedback?

You can send feedback at support.datasf.org.
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Data Lifecycle
Last modified 3yr ago
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Outline
What is data quality?
What is the purpose of this guide?
Why does data quality matter?
How can I use this guide?
Who should use this guide?
What background do I need for this guide?
How can I provide feedback?