Interested in a simple Skills Scan and Learning Progress Tracker tool for the Data technician standard?
Knowledge
K1: Range of different types of existing data. Common sources of data - internal, external, open data sets, public and private. Data formats and their importance for analysis. Data architecture - the framework against which data is stored and structured including on premises and cloud.
K2: How to access and extract data from a range of already identified sources
K3: How to collate and format data in line with industry standards
K4: Data formats and their importance for analysis Management and presentation tools to visualise and review the characteristics of data Communication tools and technologies for collaborative working
K5: Communication methods, formats and techniques, including: written, verbal, non-verbal, presentation, email, conversation, audience and active listening Range of roles within an organisation, including: customer, manager, client, peer, technical and non-technical
K6: The value of data to the business How to undertake blending of data from multiple sources
K7: Algorithms, and how they work using a step-by-step solution to a problem, or rules to follow to solve the problem and the potential to use automation
K8: How to filter details, focusing on information relevant to the data project
K9: Basic statistical methods and simple data modelling to extract relevant data and normalise unstructured data
K10: The range of common data quality issues that can arise e.g. misclassification, duplicate entries, spelling errors, obsolete data, compliance issues and interpretation/ translation of meaning
K11: Different methods of validating data and the importance of taking corrective action
K12: Communicating the results through basic narrative
K13: Legal and regulatory requirements e.g. Data Protection, Data Security, Intellectual Property Rights (IPR), Data sharing, marketing consent, personal data definition. The ethical use of data
K14: The significance of customer issues, problems, business value, brand awareness, cultural awareness/ diversity, accessibility, internal/ external audience, level of technical knowledge and profile in a business context
K15: The role of data in the context of of the digital world including the use of eternal trusted open data sets, how data underpins every digital interaction and connectedness across the digital landscape including applications, devises, IoT, customer centricity
K16: Different learning techniques, learning techniques and the breadth and sources of knowledge
Skills
S1: Source and migrate data from already identified different sources
S2: Collect, format and save datasets
S3: Summarise and explain gathered data
S4: Blend data sets from multiple sources and present in format appropriate to the task
S5: Manipulate and link different data sets as required
S6: Use tools and techniques to identify trends and patterns in data
S7: Apply basic statistical methods and algorithms to identify trends and patterns in data
S8: Apply cross checking techniques for identifying faults and data results for data project requirements
S9: Audit data results
S10: Demonstrate the different ways of communicating meaning from data in line with audience requirements
S11: Produce clear and consistent technical documentation using standard organisational templates
S12: Store, manage and distribute in compliance with data security standards and legislation
S13: Explain data and results to different audiences in a way that aids understanding.
S14: Review own development needs
S15: Keep up to date with developments in technologies, trends and innovation using a range of sources
S16: Clean data i.e. remove duplicates, typos, duplicate entries, out of date data, parse data (e.g. format telephone numbers according to a national standard) and test and assess confidence in the data and its integrity.
S17: Operate as part of a multi-functional team
S18: Prioritise within the context of a project
Behaviours
B1: Manage own time to meet deadlines and manage stakeholder expectations
B2: Work independently and take responsibility
B3: Use own initiative
B4: A thorough and organised approach
B5: Work with a range of internal and external customers
B6: Value difference and be sensitive to the needs of others
Duty 1
DUTY: source data from a collection of already identified trusted sources in a secure manner
CRITERIA FOR MEASURING PERFORMANCE: Data is collected securely from trusted sources in line with current company requirements informed by relevant regulatory and legal standards and industry best practice
K1
K2
K15
S1
B1
B2
B4
Duty 2
DUTY: collate and format data to facilitate processing and presentation for review and further advanced analysis by others
CRITERIA FOR MEASURING PERFORMANCE: Data collated and formatted according to company procedures and recognised industry good practice
K3
S2
S16
B1
B2
B4
Duty 3
DUTY: present data for review and analysis by others, using required medium for example tables, charts and graphs
CRITERIA FOR MEASURING PERFORMANCE: Data is presented in an appropriate format for review and analysis in line with company procedures and industry best practice.
K4
K5
S3
B5
B6
Duty 4
DUTY: blend data by combining data from various sources and formats to explore its relevance for the business needs
CRITERIA FOR MEASURING PERFORMANCE: Data is blended ensuring that accuracy and consistency is maintained in line with current company requirements informed by relevant regulatory and legal standards and industry best practice
K6
S4
S5
S6
S16
B1
B2
B4
Duty 5
DUTY: analyse simple and complex structured and unstructured data to support business outcomes using basic statistical methods to analyse the data.
CRITERIA FOR MEASURING PERFORMANCE: Data is structured in a way that meets business outcomes
K7
K8
K9
S7
B1
B2
B3
B4
B5
B6
Duty 6
DUTY: validate results of analysis using various techniques, e.g cross checking, to identify faults in data results and to ensure data quality
CRITERIA FOR MEASURING PERFORMANCE: Results are validated in line with organisation and project data quality requirements
K10
K11
S8
S9
S16
B1
B2
B3
B4
Duty 7
DUTY: communicate results verbally, through reports and technical documentation and tailoring the message for the audience
CRITERIA FOR MEASURING PERFORMANCE: Results from data communicated in line with audience requirements
K5
K12
S10
S11
B5
B6
Duty 8
DUTY: store, manage and share data securely in a compliant manner
CRITERIA FOR MEASURING PERFORMANCE: Data is stored, managed and shared in line with organisation, legal and regulatory requirements
K13
S12
S15
B4
Duty 9
DUTY: collaborate with people both internally and externally at all levels with a view to creating value from data
CRITERIA FOR MEASURING PERFORMANCE: The employee is able to confidently engage with people internally and externally at all levels in a professional manner
K14
S13
S15
S16
S17
S18
B2
B5
B6
Duty 10
DUTY: practise continuous self learning to keep up to date with technological developments to enhance relevant skills and take responsibility for own professional development
CRITERIA FOR MEASURING PERFORMANCE: Articulate the latest technology trends affecting data analysis and can communicate the impacts of latest trends
