This occupation is found in all sectors where data is generated or processed including but not limited to finance, retail, education, health, media, manufacturing and hospitality. The broad purpose of the occupation is to source, format and present data securely in a relevant way for analysis using basic methods; to communicate outcomes appropriate to the audience; analyse structured and unstructured data to support business outcomes; blend data from multiple sources as directed and apply legal and ethical principles when manipulating data. In their daily work, an employee in this occupation interacts with a wide range of stakeholders including colleagues, managers, customers and internal and external suppliers. 

What the course leads to

What courses can I do after this? 

What jobs can I get? 

Data Analyst, Data Technician, Information Analyst

What do I need to apply

To do this course you should have... 

Candidates will likely require five GCSEs at grades 9-4, (especially English, Mathematics and a Science or Technology subject), a relevant Level 3 Apprenticeship or other relevant qualifications and experience.

What about work experience? 

Not Essential

Course costs

Course Code Start Date Costs 16-18 Costs 19-23 (with concessions) Costs 19+ (no concessions)
DTX5HC0385 01/08/2021 TBC TBC TBC

* Please note fees are subject to change.

Course content

Course Content 

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

More info

Start Day/Time 

September 2021

Duration 

24 Months

Attendance 

Full-time

Level 

Level 3

Qualification Name 

Apprenticeship

Awarding Body 

British Computer Society

Curriculum Area 

Business, Digital, Leadership & ESOL - Digital & Computing

More about the course 

Typical job duties include:

Duty 1 Source data from a collection of already identified trusted sources in a secure manner

Duty 2 Collate and format data to facilitate processing and presentation for review and further advanced analysis by others

Duty 3 Present data for review and analysis by others, using required medium for example tables, charts and graphs

Duty 4 Blend data by combining data from various sources and formats to explore its relevance for the business needs

Duty 5 Analyse simple and complex structured and unstructured data to support business outcomes using basic statistical methods to analyse the data.

Duty 6 Validate results of analysis using various techniques, e.g cross checking, to identify faults in data results and to ensure data quality

Duty 7 Communicate results verbally, through reports and technical documentation and tailoring the message for the audience

Duty 8 Store, manage and share data securely in a compliant manner

Duty 9 Collaborate with people both internally and externally at all levels with a view to creating value from data

Duty 10 Practise continuous self learning to keep up to date with technological developments to enhance relevant skills and take responsibility for own professional development

 

 

Duration 

24 Months

Attendance 

Full-time

Level 

Level 3

Qualification Name 

Apprenticeship

Awarding Body 

British Computer Society