Data modelling, cleansing and enrichment

引自 UK GDaD PCF。

等级

1. 了解

You can:

• show an awareness of different data models and tools, and understand when they could be used
• show an awareness of industry-recognised data modelling patterns and standards

2. 胜任

You can:

• produce data models and understand where to use different types of data models
• understand different tools and can compare different data models
• reverse-engineer a data model from a live system
• understand industry-recognised data modelling patterns and standards

3. 熟练

You can:

• build and review complex data models, ensuring adherence to standards
• use data integration tools and languages to integrate and store data, and advise teams on best practice
• ensure data for analysis meets data quality standards and is interoperable with other data sets, enabling reuse
• work with other data professionals to improve modelling and integration patterns and standards

4. 专家

You can:

• understand different ways to model data to maximise its use and value
• ensure data is modelled appropriately, and modelling standards exist and are complied with
• understand a number of data integration tools and patterns, and ensure your teams have the support and training needed to use the most appropriate methods
• build relationships with other senior data professionals (in fields such as data architecture, data engineering and data science) to share best practice and continually improve data modelling and integration processes and standards

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.

最接近的 ESCO 技能

• create data models (接近匹配)
• perform data cleansing (狭义匹配)
• normalise data (狭义匹配)

Contains ESCO v1.2.1 data (https://esco.ec.europa.eu/). © European Union. Reuse authorised under Commission Decision 2011/833/EU.

期望具备该技能的角色级别