This skills scan is made up of two parts. The first section focuses on how you think data skills will add value to your role by asking you how frequently you perform some common tasks. You may not currently be required to perform all or any of these tasks in your role. The second is a self-evaluation which provides us with a skills benchmark for each of the competencies that form the Corndel Data Analytics Diploma.
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Advanced: I use simple functions, such as UPPER, or wildcards. I use several different aggregating functions. I combine aggregation, multiple joins, and sub-queries to manipulate data into the required format.
Advanced: I understand how to set constraints, set primary keys, and create indexes within a relational database. I use non-table objects within a relational database, such as views, types, and functions.
Advanced: I know and use a range of tools that can be used for data preparation. I know a range of techniques to standardise variables and remove correlated variables. I understand how to use over- and under- sampling appropriately.
Advanced: I build both linear regression and logistic regression models, to predict either quantitative outcomes or binary outcomes. I use clustering algorithms, such as the k-means algorithm, to group similar data points together. I interpret complex regression and clustering models to generate insight and inform business activities.
Advanced: I can systematically break down time series data into seasonal, trend, or moving average components. I use time series data to quantify the impact of past events. I understand the ARIMA model and can apply it to make short-term forecasts.
Advanced: I advise on the transformation of information from one format/medium to another, where appropriate. I collect data in the appropriate format to support moderately complex analysis. I transform data into a different format, when needed.
Advanced: I use of a range of appropriate data integration techniques. I design automated data integration processes, with other people in mind. I build ETL pipelines in line with my organisation's data architecture.
Advanced: I apply formal data structures and protection measures, to ensure that information is available and searchable. I identify gaps in the available information and devise ways to resolve these gaps. I advise others on data quality procedures.
Advanced: I consistently apply the full range of existing organisational standards and policies. I participate in the development and maintenance of corporate data standards. I advise others on data compliance and ethics.
Advanced: I understand the concepts of Big data technology, including Hadoop and MapReduce. I can explain the strengths/weaknesses of Big data technologies vs relational databases.
Advanced: I interview stakeholders to better understand requirements. I define testable hypotheses and success criteria from the outset of a project. I proactively refine project briefs using my data expertise to advise stakeholders on requirements. I design interactive and intuitive dashboards.
Advanced: I apply information handling procedures when communicating insights. I understand how humans process information and consistently apply data visualisation best practice. I explain outcomes in a range of formats, including written and spoken, depending on the audience.
Advanced: I can evaluate the strengths and weaknesses of competing data architectures. I demonstrate tools and facilities to colleagues and others. I proactively ensure that appropriate standards for repository administration and data dictionaries are observed. I identify and communicate opportunities for improved data management.
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