Quality assurance of data and analysis

UK GDaD PCF থেকে উদ্ধৃত।

স্তর

1. সচেতনতা

You can:

• describe some basic data issues and how to check that data and analysis look right
• explain the concept of data being fit for purpose, and the context of the data
• describe some methods for preparing data for analysis
• describe quality assurance processes

2. কার্যকর

You can:

• identify appropriate ways to collect, collate and prepare data
• decide if data and analysis is accurate and fit for purpose
• perform data preparation and cleansing with limited guidance
• undertake quality assurance processes
• peer-review colleagues’ outputs from data analysis to ensure quality

3. অনুশীলনকারী

You can:

• set up a system to get data ready for use
• specify how data should be cleansed and prepared
• bring data together from different sources
• communicate the limitations of data

4. বিশেষজ্ঞ

You can:

• set up tools and systems for effectively assuring data and analysis across multiple teams
• use appropriate approaches for verifying and validating data and analysis
• influence senior stakeholders over data and analysis approaches
• coach and mentor others in assuring data and analysis

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.

সবচেয়ে কাছের ESCO দক্ষতা

• implement data quality processes (কাছাকাছি মিল)
• data quality assessment (কাছাকাছি মিল)
• perform data cleansing (সংকীর্ণ মিল)

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

যে ভূমিকার স্তরগুলো এই দক্ষতা প্রত্যাশা করে