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Data Analyst
Published
Competency-Based Apprenticeship
Industries
O*Net Code
15-2041.00
Rapids Code
2099CB
Req. Hours
0
State
DC
Created
Jul 16, 2021
Updated
Jul 16, 2021
Competency-Based Skills
15 skill sets | 67 total skills
Understand, articulate, and demonstrate basic statistical concepts.
Identify definitions of central tendency and dispersion.
Recognize the difference between descriptive and inferential statistics.
Calculate 3 measures of central tendency in a sample – mean, median, and mode.
Calculate 1 measure of dispersion in a sample – standard deviation.
Identify a continuous distribution vs. a discrete distribution.
Carry out hypothesis tests and working with p-values.
Recognize the attributes of Type I and Type II errors.
Understand, articulate, and demonstrate knowledge of statistical tools programs.
Identify common statistical packages for data analysts in R or Python.
Understand, articulate, and demonstrate knowledge of Agile principles and concepts.
Distinguish between the Agile practices of the social contract, standups, and retrospectives.
Articulate the differences between the Agile concepts of the scrum, sprint, and time boxes.
Demonstrate knowledge of how Agile teams work in a self-directed manner.
Identify the types of information revealed by value stream mapping.
Identify activities carried out during a value stream mapping.
Understand, articulate, and demonstrate knowledge of data science principles.
Distinguish between accuracy and precision.
Recognize the importance of finding the statistical significance of correlation.
Recognize how linear regression is used during data analysis.
Classify examples of causes of variations as either common or special causes.
Understand, articulate, and demonstrate processing data for data analysis
Identify any missing values and outliers.
Ensure the integrity of data (e.g., appropriate data types, values that don’t make sense).
Identify steps to process data for data analysis.
Use appropriate data tools to process data for data analysis.
Use statistical knowledge and charts to prepare a data analysis report.
Articulate and demonstrate successful use of data analyst tool packages.
Recognize how to use probability distributions and control charts in data analysis.
Match the key elements of a control chart with corresponding descriptions.
Apply decision rules to given run charts.
Sequence the steps for creating a Pareto chart.
Understand, articulate, and demonstrate knowledge of Lean Six Sigma concepts.
Recognize how the 5 Whys is used for root cause analysis.
Classify examples of value and non-value-added activities and waste.
Sequence examples of activities that happen during the Kaizen process.
Demonstrate knowledge of data visualization techniques.
Interpret a histogram.
Use scatterplots, line graphs, bar charts, histograms, box plots, area charts, and heat maps.
Identify principles of chart consistency, simplicity, and clarity.
Understand, articulate, and demonstrate knowledge of ITIL Foundation concepts (or industry relevant applicable concepts can be substituted here).
Identify features of a service.
Recognize the purpose of each ITIL service lifecycle stage.
Distinguish between functions and processes.
Identify recommended incident management principles.
Recognize the scope of the problem management process.
Distinguish between the three types of changes in the change management process.
Identify challenges of service portfolio management.
Recognize the considerations to make when implementing service improvements.
Ability to present data analysis to stakeholders through storytelling methods.
Identify the 4 components of presenting actionable insights.
Understand how executive communication differs from standard reporting.
Use the Theory of a Slide to develop a presentation.
Apply a pyramid design to a presentation.
Articulate knowledge of design thinking concepts.
Extract data insights and prepare data for analysis.
Distinguish between examples of qualitative and quantitative data.
Identify principles of data sampling.
Recognize principles of effective data collection.
Match technologies used for data collection with their corresponding characteristics.
Distinguish between metadata and data.
Use a tool to extract tabular data, data from a spreadsheet, and convert a spreadsheet to CSV.
Extract date elements from common date formats.
Drop duplicate records from data.
Detect invalid or impossible data combinations.
Read various data formats and convert to standard compliant ISO 8601 format.
Demonstrate knowledge of information technology business skills and concepts.
Demonstrate an understanding of basic security and cognitive computing concepts.
Demonstrate strong communication skills.
Demonstrate strong communication skills through the selection of the appropriate communication method for each message.
Demonstrate strong presentation skills through quality materials and clear presentation.
Demonstrate appropriate verbal communication skills through stand-ups, cadence calls, and one-on-one conversations with managers and other stakeholders.
Understand and model good feedback behaviors.
Understand the importance of feedback in all we do.
Successfully leverage Net Promoter Score methodology.
Deliver quality feedback to team members.
Receive feedback gracefully and act on it
Model goal setting behaviors through performance management system.
Model a culture of feedback with all team members.
Demonstrate key teamwork and collaborative behaviors
Collaborate with other members of team to deliver an outstanding client experiences.
Partner successfully in delivering key business outcomes.
