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Data Analyst
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Course sections

Section 1
COURSE INTRODUCTION
1
Logistics, materials, and course expectations
2
Agile and integrated set of tools and best practices
3
References and resources
Section 2
INTRODUCTION TO DATA ANALYSIS AND DATA ANALYTICS
1
Definition and history
2
Current technology, the growing availability of data, and increasing challenges
3
Applications for gaining competitive advantages
Section 3
RETHINKING THE VALUE AND USAGE OF DATA
1
The impact of vast volumes of available data especially for decision making
2
Data difficulties and limitations: ROI vs. effort/expense, incomplete and inconclusive data
3
Dealing with data uncertainty
4
Getting real value out of your data: The data continuum
5
Effective and responsible data ownership
6
Advantages and disadvantages of qualitative and quantitative data types
7
Solutions and best practices to transform the way your organization accesses and uses data
8
Organizing the entire organization’s data for maximum efficiency using easily available tools
9
Taking advantage of the expertise of the entire organization
Section 4
INTRODUCTION TO DATA MINING AND DATA WAREHOUSING
1
Data Mining concepts and application
2
Application benefits of data warehousing
Section 5
DATA DISTRIBUTION AND VARIANCE
1
Decision making under uncertainty
2
Probability
3
Data distribution
4
Variance
5
Standard deviation
Section 6
INFORMATION NEEDS
1
Operational and executive information classes?
2
Key functional transactions and documents
3
Map information needs to underlying data
4
Executive information needs and the balanced scorecard
5
Role of the business analyst and data analyst
6
How to use simple pivot tables in Excel or Google Sheets to analyze and present your data
7
Tracking and managing business process performance
8
Learning from data
Section 7
DATA EXPLORATION CONCEPTS AND METHODS
1
Basic concepts
2
Descriptive measures of a sample
3
Histograms
4
Statistical hypothesis and inference
5
Dependence and correlation
6
Moving beyond data and decision uncertainty – managing risk
Section 8
FORECASTING
1
Forecasting methods and models
2
Time series analysis
3
Linear regression
4
Establishing trends and business cycles (i.e., seasonality)
5
Selecting independent variables for predictive models including regression techniques
Section 9
REVIEW
Section 10
BEST PRACTICES AND NEXT STEPS
1
Data analysis and transformation
2
Best practices revisited
3
Next steps options
Section 11
COURSE CLOSEOUT
1
Putting It All Together. The Value of Powerful Data
Section 12
Additional Resources and Exercises
1
Additional Resources and Exercises
Section 13
WHO SHOULD ATTEND
1
Individuals who are interested in operations, project management, business analysis, or management, who need an introduction to data analysis

WHO SHOULD ATTEND

Individuals who are interested in operations, project management, business analysis, or management, who need an introduction to data analysis

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