Course Outline

Introduction to Data Management for Government

  • Overview of data handling and storage practices
  • Fundamentals of database management and table creation
  • Introduction to relational models and their application in government operations

Basic Data Analysis Techniques for Government

  • Descriptive statistics and distribution analysis
  • Histograms and control charts for quality assurance
  • Data stratification and processing methods for efficient governance

Data Modeling for Decision-Making in Government

  • Introduction to data modeling concepts tailored for government use
  • Calendar tables and hierarchical structures for better data organization
  • Field relationships and table joins for comprehensive data integration

Dynamic Reporting Tools for Government

  • Using Excel, Power Query, and DAX for data manipulation
  • Creating interactive dashboards in Excel for real-time reporting
  • Editing and sourcing data with Power Pivot for enhanced analysis

Applied Statistical Techniques for Government

  • Basic regression and classification methods for policy evaluation
  • Prediction models and their interpretation for strategic planning
  • Practical data analysis scenarios relevant to public sector operations

Introduction to Data Science Concepts for Government

  • Fundamentals of data science in the context of government services
  • Tools for detecting patterns and trends in public data
  • Simple machine learning techniques for predictive analytics in governance

Data-Driven Decision-Making for Government

  • Evaluating reports to inform policy decisions
  • Communicating analytical results effectively to stakeholders
  • Case studies and real-world applications of data-driven approaches in government

Summary and Next Steps for Government

Requirements

  • An understanding of fundamental computer operations
  • Experience with spreadsheets and basic data formats
  • Familiarity with Microsoft Office tools

Audience for Government

  • Environmental protection managers
  • Data engineers and analysts
  • Professionals seeking data-driven decision-making tools
 30 Hours

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