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Data Analytics
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Module 1
Analytical Thinking and Data Foundations
1
Turning Stakeholder Requests into Answerable Analysis Questions
Translate a stakeholder request into one specific, answerable analysis question.
Translate a stakeholder request into one specific, answerable analysis question.
2
Identifying a Dataset’s Unit of Analysis
Identify the unit of analysis, or grain, represented by each row of a dataset.
Identify the unit of analysis, or grain, represented by each row of a dataset.
3
Classifying Dataset Fields: Identifiers, Dimensions, Measures, and Dates
Classify dataset fields as identifiers, dimensions, measures, or dates.
Classify dataset fields as identifiers, dimensions, measures, or dates.
4
Defining KPIs with Formulas, Units, Aggregation Levels, and Time Periods
Define a KPI with an explicit formula, unit, aggregation level, and time period.
Define a KPI with an explicit formula, unit, aggregation level, and time period.
5
Creating a Data Dictionary: Field Definitions and Valid Values
Create a data dictionary that documents field meanings and valid values.
Create a data dictionary that documents field meanings and valid values.
6
Dataset Profiling: Missing Values and Duplicate Records
Profile a dataset to quantify missing values and duplicate records.
Profile a dataset to quantify missing values and duplicate records.
7
Mapping Business Questions to Analysis Plans
Write an analysis plan that maps a business question to required fields, calculations, and outputs.
Write an analysis plan that maps a business question to required fields, calculations, and outputs.
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