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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.
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K2: How to access and extract data from a range of already identified sources
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K3: How to collate and format data in line with industry standards
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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
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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
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K6: The value of data to the business How to undertake blending of data from multiple sources
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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
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K8: How to filter details, focusing on information relevant to the data project
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K9: Basic statistical methods and simple data modelling to extract relevant data and normalise unstructured data
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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
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K11: Different methods of validating data and the importance of taking corrective action
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K12: Communicating the results through basic narrative
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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
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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
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K16: Different learning techniques, learning techniques and the breadth and sources of knowledge