Data preparation and linkage
Data preparation and linkage involves cleansing, modelling, transforming and assuring the quality of data so that it is usable and reproducible.
수준
- 1. 인지
You can:
- explain the importance of data models and their uses
- identify appropriate channels in your organisation to learn about data modelling and quality standards
- identify data quality issues and provide possible solutions to resolve them
- prepare and cleanse data under supervision, contributing to making it fit for purpose
- 2. 실무
You can:
- support the planning of a data model based on appropriate data sources
- help ensure new and existing data models and pipelines can be reused or reproduced
- identify and resolve data quality issues
- prepare and cleanse data, ensuring it is fit for purpose
- 3. 실천가
You can:
- plan the framework of an analytical data model based on appropriate data sources
- support the implementation of data models using appropriate tools and systems
- ensure your team understands the importance of data quality and modelling
- 4. 전문가
You can:
- develop analytical data models using a deep understanding of data sources
- ensure data models are implemented using tools and systems that align with modelling standards
- set data quality standards in the organisation or beyond, and ensure stakeholders understand their importance
- mentor others in data quality and modelling
Contains public sector information from the UK Government Digital and Data Profession Capability Framework (https://understand-digital-data-roles-skills.service.gov.uk/), licensed under the Open Government Licence v3.0. © Crown copyright.
가장 가까운 ESCO 스킬
Contains ESCO v1.2.1 data (https://esco.ec.europa.eu/). © European Union. Reuse authorised under Commission Decision 2011/833/EU.
이 스킬을 기대하는 역할 수준
| 역할 수준 | 역할 | 밴드 | 기대 수준 |
|---|---|---|---|
| 어소시에이트 데이터 분석가 | 데이터 분석가 | 5 | 인지 |
| 데이터 분석가 | 데이터 분석가 | 6 | 실무 |
| 시니어 데이터 분석가 | 데이터 분석가 | 7 | 실천가 |
| 프린시펄 데이터 분석가 | 데이터 분석가 | 8b | 전문가 |