Best Data Analysis Courses Online

Data Analysis Online Training with Placement

Course Content:

Course Introduction:

• Logistics, materials, and course expectations
• Agile and integrated (A&I) set of tools and best practices
• References and resources

Introduction to Data Analysis and Analytics:

• Definition and history
• Current technology, the growing availability of data, and increasing challenges
• Applications for gaining competitive advantages

Rethinking the Value and Usage of Data:

• The impact of vast volumes of available data especially for decision making
• Data difficulties and limitations: ROI vs. effort/expense, incomplete and inconclusive data
• Dealing with data uncertainty
• Getting real value out of your data: The data continuum
• Effective and responsible data ownership
• Advantages and disadvantages of qualitative and quantitative data types
• Solutions and best practices to transform the way your organization accesses and uses data
• Organizing the entire organization's data for maximum efficiency using easily available tools
• Taking advantage of the expertise of the entire organization

Introduction to Data Mining and Data Warehousing:

• Data Mining concepts and application
• Application benefits of data warehousing

Data Distribution and Variance:

• Decision making under uncertainty
• Probability
• Data distribution
• Variance
• Standard deviation

Information Needs:

• Operational and executive information classes
• Key functional transactions and documents
• Map information needs to underlying data
• Executive information needs and the balanced scorecard
• Role of the business analyst and data analyst
• How to use simple pivot tables in Excel or Google Sheets to analyze and present your data
• Tracking and managing business process performance
• Learning from data

Data Exploration Concepts and Methods:

• Basic concepts
• Descriptive measures of a sample
• Histograms
• Statistical hypothesis and inference
• Dependence and correlation
• Moving beyond data and decision uncertainty - managing risk

Forecasting:

• Forecasting methods and models
• Time series analysis
• Linear regression
• Establishing trends and business cycles (i.e., seasonality)
• Selecting independent variables for predictive models including regression techniques

Review, Best Practices, and Next Steps:

• Data analysis and transformation
• Best practices revisited
• Next steps options

Course Closeout: Putting It All Together. The Value of Powerful Data

Additional Resources and Exercises