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Skill Details

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Skill Overview

University Academy 92 (UA92) is a deliberately different and game-changing higher education establishment located at a new campus in Old Trafford, Manchester, offering apprenticeships, bootcamps and degrees awarded by Lancaster University.
Co-founded by the infamous Manchester United legends the Class of 92 (Gary and Phil Neville, Ryan Giggs, Paul Scholes and Nicky Butt), and Lancaster University, UA92 offers character and personal development at the core of their learning experience along, with a curriculum co-developed by employers.
UA92 aims to develop students’ resilience, alongside their ability to solve problems and face challenges and aims to prepare them for life.
Data Technicians are found in all sectors where data is generated or processed. The broad purpose of a Data Technician 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, a Data Technician interacts with a wide range of stakeholders including colleagues, managers, customers and internal and external suppliers. They would typically work as a member of a team; this may be office based or virtual. A Data Technician will be responsible for collecting and processing data under the guidance of a senior colleague or multiple colleagues across the business. This may vary by sector and size of the organisation. A Data Technician would mainly be responsible for their own work but may have the opportunity to mentor others.

Learning Objectives

Source data from a collection of already identified trusted sources in a secure manner.
Collate and format data to facilitate processing and presentation for review and further advanced analysis by others.
Present data for review and analysis by others, using required medium for example tables, charts and graphs.
Blend data by combining data from various sources and formats to explore its relevance for the business needs.
Analyse simple and complex structured and unstructured data to support business outcomes using basic statistical methods to analyse the data.
Validate results of analysis using various techniques, to identify faults in data results and to ensure data quality.
Communicate results verbally, through reports and technical documentation and tailoring the message for the audience.
Store, manage and share data securely in a compliant manner.
Collaborate with people both internally and externally at all levels with a view to creating value from data.
Practise continuous self learning to keep up to date with technological developments to enhance relevant skills and take responsibility for own professional development.

Funding Option

Funding Eligibility

For apprentices aged 16-21 the training costs are fully funded by the government. For apprentices aged over 21, there is a 5% co-investment which would be paid by the employer. Alternatively, the training costs can be covered by utilising the Apprenticeship Levy Fund.

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