"*" indicates required fields 1Details2Knowledge3Skills4Behaviours5Qualifications, Prior Learning & Experience Welcome to the Corndel Data Analyst Level 4 Skills Radar. This skills radar is a self assessment tool that is used to confirm your eligibility for this apprenticeship, and to help us to understand your current level of knowledge, skills and behaviours against those of this programme. If you hold qualifications, or have prior learning or experience related to this programme we will contact you to discuss this further, as you may not be eligible for government funding. Unique IDHiddenDate of completion DD slash MM slash YYYY HiddenAlteryx yes Your detailsName* First Last Aptem email address* Enter Email Confirm Email Employer* Job title* Your data will be processed by Corndel in accordance with their Privacy Policy.Privacy policy* Please tick here to confirm your consent* The statements below cover the knowledge that you will learn and develop on this programme. Using the 1-10 guidance below, please assess your current level of knowledge and experience in relation to the level of this programme. 1-2: I have no prior learning or experience and cannot demonstrate this. 3-4: I have some prior learning or experience and demonstrate this inconsistently. 5-6: I have moderate prior learning or experience and demonstrate this occasionally. 7-8: I have good, or very good prior learning or experience and demonstrate this often. 9: I have extensive prior learning or experience and demonstrate this to an exemplary standard. 10: I am an expert and have nothing further to learn. Knowledge - Part 1:*12345678910Current relevant legislation and its application to the safe use of data.The ethical aspects associated with the use and collation of data.Organisational data and information security standards, policies and procedures relevant to data management activities.Principles of data, including open and public data, administrative data, and research data.The fundamentals of data structures, database system design, implementation and maintenance.Organisational data architecture.The differences between structured and unstructured data.Quality risks inherent in data and how to mitigate or resolve these.Approaches to combining data from different sources.Knowledge - Part 2:*12345678910Principles of user experience and domain context for data analytics.Principal approaches to defining customer requirements for data analysis.Principles of statistics for analysing datasets.Principles of descriptive, predictive and prescriptive analytics.Principles of the data life cycle and the steps involved in carrying out routine data analysis tasks.Approaches to organisational tools and methods for data analysis. The statements below cover the skills that you will learn and develop on this programme. Using the 1-10 guidance below, please assess your current level of skills and experience in relation to the level of this programme. 1-2: I have no prior learning or experience and cannot demonstrate this. 3-4: I have some prior learning or experience and demonstrate this inconsistently. 5-6: I have moderate prior learning or experience and demonstrate this occasionally. 7-8: I have good, or very good prior learning or experience and demonstrate this often. 9: I have extensive prior learning or experience and demonstrate this to an exemplary standard. 10: I am an expert and have nothing further to learn. Skills - Part 1:*12345678910Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design.Undertake customer requirements analysis and implement findings in data analytics planning and outputs.Identify data sources and the risks and challenges to combination within data analysis activity.Implement the stages of the data analysis lifecycle.Apply organisational architecture requirements to data analysis activities.Apply principles of data classification within data analysis activity.Select and apply the most appropriate data tools to achieve the optimum outcome.Skills - Part 2:*12345678910Apply predictive analytics in the collation and use of data.Apply statistical methodologies to data analysis tasks.Analyse data sets taking account of different data structures and database designs.Use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data.Identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate.Assess the impact on user experience and domain context on data analysis activity.Collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs.Collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience. The statements below cover the behaviours that you will learn and develop on this programme. Using the 1-10 guidance below, please assess your current level against the behaviours, in relation to the level of this programme. 1-2: I have no prior learning or experience and cannot demonstrate this. 3-4: I have some prior learning or experience and demonstrate this inconsistently. 5-6: I have moderate prior learning or experience and demonstrate this occasionally. 7-8: I have good, or very good prior learning or experience and demonstrate this often. 9: I have extensive prior learning or experience and demonstrate this to an exemplary standard. 10: I am an expert and have nothing further to learn. Behaviours:*12345678910Maintains a productive, professional and secure working environment.Shows initiative, being resourceful when faced with a problem and taking responsibility for solving problems within their own remit.Works independently and collaboratively.Logical and analytical.Identifies issues quickly, investigating and solving complex problems and applying appropriate solutions. Ensures the true root cause of any problem is found and a solution is identified which prevents recurrence.Resilient - viewing obstacles as challenges and learning from failure.Adaptable to changing contexts within the scope of a project, direction of the organisation or Data Analyst role. Have you previously achieved a qualification equivalent to a level 4 (e.g. certificate of higher education (CertHE) and/or higher national certificate (HNC) or above?* Yes No Please list all relevant qualifications*Click on the (+) to add further qualificationsTitleLevel Add RemoveOther work experience Tick here if you have any other work experience that may be relevant to this apprenticeship that could affect your eligibility. Please provide details:* SignatureHiddenDate DD slash MM slash YYYY
