Introduction:

 Economic Data Management and Analytics is a comprehensive course designed to equip participants with the necessary skills and knowledge to effectively manage and analyze economic data. This course focuses on the principles and techniques used in collecting, organizing, analyzing, and interpreting economic data for decision-making purposes. Participants will gain hands-on experience with various tools and methods commonly used in economic data management and analysis.

Course Objectives:

1. Understand the importance of economic data management and analytics in decision-making processes.
2. Develop proficiency in collecting, organizing, and managing economic data.
3. Learn various statistical techniques and methods for analyzing economic data.
4. Gain hands-on experience with data visualization tools and techniques.
5. Enhance skills in interpreting and communicating economic data effectively.
6. Explore advanced topics in economic data management and analytics.

Organizational Benefits:

 By enrolling employees in the Economic Data Management and Analytics course, organizations can expect the following benefits:

1. Improved decision-making: Participants will acquire skills to effectively analyze economic data, enabling informed decision-making that aligns with organizational objectives.
2. Enhanced data management practices: The course equips participants with best practices for collecting, organizing, and managing economic data, leading to improved data quality and reliability.
3. Increased efficiency: With the ability to analyze and interpret economic data accurately, employees can identify trends, patterns, and insights more efficiently, facilitating proactive decision-making.
4. Better communication: Participants will learn to present complex economic data in a clear and concise manner, enabling effective communication with stakeholders.
5. Competitive advantage: Organizations that can leverage economic data effectively are better equipped to identify market opportunities, mitigate risks, and gain a competitive edge.

Duration:

10 days

1. Module 1: Introduction to Economic Data Management and Analytics
• Understanding the importance of economic data
• Overview of data management and analytics in economics
• Role of economic data in decision-making and policy formulation
2. Module 2: Basics of Data Collection in Economics
• Primary data collection methods
• Secondary data collection methods
• Sampling techniques and survey design
3. Module 3: Data Types and Sources in Economics
• Different types of economic data (cross-sectional, time series, panel)
• Sources of economic data (government agencies, international organizations, private databases)
4. Module 4: Data Cleaning and Preprocessing Techniques
• Identifying and handling missing data
• Outlier detection and treatment
• Data transformation and normalization techniques
5. Module 5: Exploratory Data Analysis (EDA) for Economic Data
• Summary statistics and descriptive analysis
• Data visualization techniques
• Identifying patterns and relationships in economic data
6. Module 6: Statistical Analysis for Economic Data
• Probability distributions and hypothesis testing
• Parametric and non-parametric tests
• Regression analysis and model diagnostics
7. Module 7: Time Series Analysis and Forecasting
• Stationarity and trend analysis
• ARIMA models
• Forecast evaluation and accuracy measures
8. Module 8: Panel Data Analysis
• Introduction to panel data
• Fixed effects and random effects models
• Panel data regression techniques
9. Module 9: Regression Analysis in Economics
• Simple and multiple linear regression
• Assumptions and diagnostics
• Interpreting regression results
10. Module 10: Multivariate Analysis Techniques
• Principal Component Analysis (PCA)
• Factor analysis
• Cluster analysis
11. Module 11: Introduction to Econometrics
• Econometric models and estimation methods
• Endogeneity and instrumental variable techniques
• Causal inference in econometrics
12. Module 12: Advanced Econometrics Techniques
• Time series econometrics (ARCH, GARCH models)
• Panel data econometrics (dynamic panel models, fixed effects vs. random effects)
• Limited dependent variable models (logit, probit)
13. Module 13: Big Data Analytics in Economics
• Handling and analyzing large-scale economic datasets
• Data mining techniques
• Machine learning algorithms for economic analysis
14. Module 14: Data Visualization for Economic Data
• Principles of effective data visualization
• Tools and software for data visualization
• Creating interactive dashboards and reports
15. Module 15: Geographic Information Systems (GIS) in Economic Analysis
• Introduction to GIS and spatial data
• Spatial analysis techniques
• Economic applications of GIS
16. Module 16: Economic Data Mining and Text Analysis
• Text mining techniques for economic data
• Sentiment analysis of economic news and reports
• Extracting insights from unstructured economic data
17. Module 17: Machine Learning for Economic Data Analysis
• Supervised and unsupervised machine learning algorithms
• Feature selection and dimensionality reduction
• Predictive modeling using machine learning
18. Module 18: Artificial Intelligence in Economic Decision-making
• Introduction to AI and its applications in economics
• AI techniques for forecasting and optimization
• Ethical considerations of AI in economic decision-making
19. Module 19: Sentiment Analysis for Economic Data
• Sentiment analysis techniques for social media and online data
• Extracting economic sentiment from textual data
• Incorporating sentiment analysis in economic analysis
20. Module 20: Risk Analysis and Management in Economics
• Types of economic risks
• Risk measurement and assessment techniques
• Risk mitigation strategies
21. Module 21: Policy Analysis using Economic Data
• Policy evaluation frameworks
• Cost-effectiveness analysis
• Policy impact assessment
22. Module 22: Economic Impact Assessment
• Assessing the economic impact of policies and projects
• Input-output analysis
• Computable General Equilibrium (CGE) models
23. Module 23: Cost-Benefit Analysis
• Principles and steps of cost-benefit analysis
• Discounting and present value calculations
• Social cost-benefit analysis
24. Module 24: Economic Modeling and Simulation
• Introduction to economic modeling
• Building and calibrating economic models
• Scenario analysis and policy simulations
25. Module 25: Ethical Considerations in Economic Data Management
• Privacy and confidentiality of economic data
• Ethical guidelines for data collection and analysis
• Handling sensitive economic information
26. Module 26: Data Security and Privacy in Economics
• Data security best practices
• Protecting economic data from unauthorized access
• Compliance with data protection regulations
27. Module 27: Data Governance and Compliance in Economics
• Data governance frameworks
• Data quality management
• Ensuring compliance with data regulations
28. Module 28: Data-driven Decision-making in Economics
• Using economic data for strategic decision-making
• Incorporating data analytics in business processes
• Real-time data analysis for agile decision-making
29. Module 29: Communicating Economic Analysis Results
• Effective presentation of economic analysis findings
• Data visualization techniques for communication
• Writing reports and policy briefs
30. Module 30: Case Studies and Practical Applications
• Applying economic data management and analytics to real-world scenarios
• Analyzing economic datasets and drawing insights
• Solving practical economic problems using data-driven approaches

General Notes

• All our courses can be Tailor-made to participants' needs
• The participant must be conversant in English
• Presentations are well-guided, practical exercises, web-based tutorials, and group work. Our facilitators are experts with more than 10 years of experience.
• Upon completion of training the participant will be issued with a Foscore development center certificate (FDC-K)
• Training will be done at the Foscore development center (FDC-K) centers. We also offer inhouse and online training on the client schedule
• Course duration is flexible and the contents can be modified to fit any number of days.
• The course fee for onsite training includes facilitation training materials, 2 coffee breaks, a buffet lunch, and a Certificate of successful completion of Training. Participants will be responsible for their own travel expenses and arrangements, airport transfers, visa application dinners, health/accident insurance, and other personal expenses.
• Accommodation, pickup, freight booking, and Visa processing arrangement, are done on request, at discounted prices.
• Tablet and Laptops are provided to participants on request as an add-on cost to the training fee.
• One-year free Consultation and Coaching provided after the course.
• Register as a group of more than two and enjoy a discount of (10% to 50%)
• Payment should be done before commence of the training or as agreed by the parties, to the FOSCORE DEVELOPMENT CENTER account, so as to enable us to prepare better for you.
• For any inquiries reach us at training@fdc-k.org or +254712260031
• Website:www.fdc-k.org