9 Topics
10 Days
45 Sessions
Programme Overview
Training Description
Who Should Attend
- Administrative coordinators
- Records and information management professionals
- Human resources and operations support staff
- Project and programme administrators
- Data and reporting support staff
- Government and public-sector administrative officers
- NGO and development-sector support professionals
- Professionals responsible for administrative reports and databases
Session Objectives
- Understand the principles of data analytics and its application in administrative roles.
- Collect and organize data from various sources.
- Use basic data analysis techniques to identify trends and patterns.
- Create data visualizations to communicate insights effectively.
- Analyze administrative processes and identify areas for improvement.
- Use data to support decision-making and problem-solving.
- Enhance their ability to improve efficiency and productivity through data analysis.
- Improve their accuracy and effectiveness in administrative tasks.
- Contribute to improved organizational performance and decision-making.
- Stay up-to-date with the latest trends and tools in data analytics.
- Become a more valuable and data-literate administrative professional.
- Understand ethical considerations in data collection and analysis.
- Learn how to use data analytics tools and software for administrative tasks.
About the Course
Data Intelligence for Administrative Professionals is a practical, skills-focused training course designed to help administrative professionals use data effectively to improve decision-making, reporting, planning, productivity, and organizational performance. The course introduces participants to essential data concepts, data collection and management, analysis, visualization, interpretation, and reporting within an administrative environment.Participants will learn how to transform routine administrative data into meaningful insights, create useful reports and dashboards, identify trends and patterns, and communicate data-driven findings clearly to managers and decision-makers.
Curriculum & Topics
9 Topics | 45 Sessions
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Workshop 1.1:
Understanding the importance of data analytics in administrative tasks.
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Workshop 1.2:
Key data analytics concepts and terminology (data types, variables, metrics).
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Workshop 1.3:
Identifying data sources and their relevance to administrative processes.
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Workshop 1.4:
The data analysis process: from data collection to insights.
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Workshop 1.5:
Ethical considerations in data handling and analysis.
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Workshop 2.1:
Collecting data from various sources (spreadsheets, databases, forms, etc.).
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Workshop 2.2:
Data entry and validation techniques.
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Workshop 2.3:
Organizing and structuring data for analysis.
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Workshop 2.4:
Cleaning and transforming data to ensure accuracy and consistency.
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Workshop 2.5:
Using spreadsheets (Excel) for basic data management.
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Workshop 3.1:
Calculating descriptive statistics (mean, median, mode, standard deviation).
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Workshop 3.2:
Identifying trends and patterns in data.
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Workshop 3.3:
Using filters and sorting to analyze data subsets.
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Workshop 3.4:
Basic data comparison and correlation analysis.
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Workshop 3.5:
Introduction to data analysis functions in Excel.
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Workshop 4.1:
Creating charts and graphs to visualize data (bar charts, line graphs, pie charts).
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Workshop 4.2:
Choosing the right visualization for different data types.
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Workshop 4.3:
Designing clear and informative data visualizations.
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Workshop 4.4:
Using data visualization to communicate insights effectively.
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Workshop 4.5:
Creating simple dashboards for tracking key metrics.
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Workshop 5.1:
Identifying key administrative processes and workflows.
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Workshop 5.2:
Collecting data on process performance and efficiency.
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Workshop 5.3:
Analyzing process bottlenecks and inefficiencies.
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Workshop 5.4:
Using data to identify areas for process improvement.
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Workshop 5.5:
Developing data-driven recommendations for process optimization.
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Workshop 6.1:
Using data to support decision-making in administrative tasks.
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Workshop 6.2:
Identifying and analyzing problems using data.
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Workshop 6.3:
Developing data-driven solutions and recommendations.
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Workshop 6.4:
Evaluating the impact of decisions using data.
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Workshop 6.5:
Using data to prioritize tasks and allocate resources.
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Workshop 7.1:
Identifying key performance indicators (KPIs) for administrative tasks.
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Workshop 7.2:
Developing reports and dashboards to track KPIs.
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Workshop 7.3:
Using data visualization to highlight key metrics and trends.
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Workshop 7.4:
Creating regular reports for management and stakeholders.
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Workshop 7.5:
Automating report generation and distribution.
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Workshop 8.1:
Using data to optimize resource allocation (time, personnel, supplies).
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Workshop 8.2:
Analyzing workflow patterns and identifying bottlenecks.
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Workshop 8.3:
Developing data-driven strategies for workflow optimization.
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Workshop 8.4:
Using data to improve scheduling and task management.
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Workshop 8.5:
Tracking and measuring the impact of resource allocation decisions.
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Workshop 9.1:
Introduction to data analytics tools and software (e.g., Power BI, Google Data Studio).
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Workshop 9.2:
Using data analytics features in spreadsheet software (Excel).
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Workshop 9.3:
Exploring online data analysis platforms and resources.
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Workshop 9.4:
Selecting and implementing appropriate data analytics tools.
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Workshop 9.5:
Continuous learning and development in data analytics.
