Detailed Course Outline
1 – Identifying Basic Concepts of Data Schemas
- Relational vs. non-relational databases
- Tables, primary keys, normalization
2 – Understanding Different Data Systems
- Types of data processing and storage
- How data changes over time
3 – Understanding Types and Characteristics of Data
- Structured vs. unstructured data
- File types and field data
4 – Comparing Data Structures, Formats, and Languages
- CSV, JSON, XML
- Common code languages used for data
5 – Data Integration and Collection
- ETL processes
- API/web scraping
- Public and survey data collection
6 – Data Cleansing and Profiling
- Handling missing or invalid data
- Converting and validating data
7 – Data Manipulation Techniques
- Querying, appending, and transforming data
- Creating calculated fields and variables
8 – Data Optimization
- Query optimization
- Efficient function use
9 – Descriptive Statistics
- Central tendency and dispersion
- Frequency and percentages
10 – Key Analytical Techniques
- Introduction to common analysis types
11 – Statistical Methods
- Hypothesis testing
- Relationships between variables
12 – Data Visualization
- Basic and advanced visuals
- Geographical data maps
- Telling stories with visuals
13 – Business Reporting Requirements
- Identifying audience needs
- Data source considerations
- Sorting and filtering
14 – Designing Reports and Dashboards
- Narrative and design elements
- Deployment considerations
15 – Deployment Considerations
- Timing, updating, and types of reports
16 – Data Governance
- Access policies
- Security and entity relationship rules
17 – Data Quality Control
- Data validation and quality metrics
18 – Master Data Management
- MDM basics and processes