Data Analyst

The primary role of a Data Analyst is to collect, organise and study data to provide business insight. Data analysts are typically involved with managing, cleansing, abstracting and aggregating data, and conducting a range of analytical studies on that data. They work across a variety of projects, providing technical data solutions to a range of stakeholders/customers issues. They document and report the results of data analysis activities making recommendations to improve business performance. They have a good understanding of data structures, database systems and procedures and the range of analytical tools used to undertake a range of different types of analyses. Candidates will cover these areas on their course: Technical Competencies Identify, collect and migrate data to/from a range of internal and external systems Manipulate and link different data sets as required Interpret and apply the organisations data and information security standards, policies and procedures to data management activities Collect and compile data from different sources Perform database queries across multiple tables to extract data for analysis Perform routine statistical analyses and ad-hoc queries 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 Assist production of performance dashboards and reports Assist with data quality checking and cleansing Apply the tools and techniques for data analysis, data visualisation and presentation Assist with the production of a range of ad-hoc and standard data analysis reports Summarise and present the results of data analysis to a range of stakeholders making recommendations Works with the organisation's data architecture Technical Knowledge and Understanding The range of data protection and legal issues The data life cycle The different types of data, including open and public data, administrative data, and research data The differences between structured and unstructured data The fundamentals of data structures, database system design, implementation and maintenance The importance of the domain context for data analytics The quality issues that can arise with data and how to avoid and/or resolve these The importance of clearly defining customer requirements for data analysis The processes and tools used for data integration The steps involved in carrying out routine data analysis tasks How to use and apply industry standard tools and methods for data analysis Underpinning Skills, Attitudes and Behaviours Logical and creative thinking skills Analytical and problem solving skills Ability to work independently and to take responsibility Can use own initiative A thorough and organised approach Ability to work with a range of internal and external people Ability to communicate effectively in a variety of situations Maintain productive, professional and secure working environment