Introduction to Data Analytics

Payroll leaders are not only responsible for maintaining extensive data and data systems but must be able to interpret and highlight payroll data insights across the organization. A foundation in data analysis, visualization and data storytelling helps payroll leaders reason critically, understand evolving business needs and issues, and deliver clear, compelling messages to payroll partners.

Topics covered: 

• Data visualization and storytelling 
• Programming languages (e.g. Python) 
• Statistics and machine learning techniques 
• Database management systems (e.g. MySQL) 

Define key concepts related to data types, data structures, and data systems used in organizational analysis. 

Describe the role of data analysis, visualization, and storytelling in supporting evidence-based decision making. 

Differentiate among qualitative and quantitative data types and structured and unstructured data sources. 

Identify appropriate data sources, collection methods, and data management practices to support analytical objectives. 

Plan operational processes to gather, clean, validate, and maintain high-quality data. 

Explain the purpose and basic capabilities of programming languages and tools commonly used for data analysis. 

Apply foundational statistical and machine learning techniques to explore patterns and relationships in data. 

Select appropriate data analysis tools, techniques, and technologies to generate meaningful business insights. 

Use database management systems to store, retrieve, and manage organizational data effectively. 

Analyze data outputs to identify trends, anomalies, and performance indicators. 

Design clear and effective data visualizations tailored to specific audiences and decision contexts. 

Translate analytical findings into compelling data stories that communicate insights and support informed decision making.