What You’ll Learn:

  • Mining data
  • Manipulating data
  • Visualizing and reporting data
  • Applying basic statistical methods
  • Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle

Course Outline:

  • IDENTIFYING BASIC CONCEPTS OF DATA SCHEMAS
    • Identify Relational and Non-Relational Databases
    • Understand the Way We Use Tables, Primary Keys, and Normalization
  • UNDERSTANDING DIFFERENT DATA SYSTEMS
    • Describe Types of Data Processing and Storage Systems
    • Explain How Data Changes
  • UNDERSTANDING TYPES AND CHARACTERISTICS OF DATA
    • Understand Types of Data
    • Break Down the Field Data Types
  • COMPARING AND CONTRASTING DIFFERENT DATA STRUCTURES, FORMATS, AND MARKUP LANGUAGES
    • Differentiate between Structured Data and Unstructured Data
    • Recognize Different File Formats
    • Understand the Different Code Languages Used for Data
  • EXPLAINING DATA INTEGRATION AND COLLECTION METHODS
    • Understand the Processes of Extracting, Transforming, and Loading Data
    • Explain API/Web Scraping and Other Collection Methods
    • Collect and Use Public and Publicly Available Data
    • Use and Collect Survey Data
  • IDENTIFYING COMMON REASONS FOR CLEANSING AND PROFILING DATA
    • Learn to Profile Data
    • Address Redundant, Duplicated, and Unnecessary Data
    • Work with Missing Values
    • Address Invalid Data
    • Convert Data to Meet Specifications
  • EXECUTING DIFFERENT DATA MANIPULATION TECHNIQUES
    • Manipulate Field Data and Create Variables
    • Transpose and Append Data
    • Query Data
  • EXPLAINING COMMON TECHNIQUES FOR DATA MANIPULATION AND OPTIMIZATION
    • Use Functions to Manipulate Data
    • Use Common Techniques for Query Optimization
  • APPLYING DESCRIPTIVE STATISTICAL METHODS
    • Use Measures of Central Tendency
    • Use Measures of Dispersion
    • Use Frequency and Percentages
  • DESCRIBING KEY ANALYSIS TECHNIQUES
    • Get Started with Analysis
    • Recognize Types of Analysis
  • UNDERSTANDING THE USE OF DIFFERENT STATISTICAL METHODS
    • Understand the Importance of Statistical Tests
    • Break Down the Hypothesis Test
    • Understand Tests and Methods to Determine Relationships Between Variables
  • USING THE APPROPRIATE TYPE OF VISUALIZATION
    • Use Basic Visuals
    • Build Advanced Visuals
    • Build Maps with Geographical Data
    • Use Visuals to Tell a Story
  • EXPRESSING BUSINESS REQUIREMENTS IN A REPORT FORMAT
    • Consider Audience Needs When Developing a Report
    • Describe Data Source Considerations For Reporting
    • Describe Considerations for Delivering Reports and Dashboards
    • Develop Reports or Dashboards
    • Understand Ways to Sort and Filter Data
  • DESIGNING COMPONENTS FOR REPORTS AND DASHBOARDS
    • Design Elements for Reports and Dashboards
    • Utilize Standard Elements
    • Creating a Narrative and Other Written Elements
    • Understand Deployment Considerations
  • DISTINGUISHING DIFFERENT REPORT TYPES
    • Understand How Updates and Timing Affect Reporting
    • Differentiate Between Types of Reports
  • SUMMARIZING THE IMPORTANCE OF DATA GOVERNANCE
    • Define Data Governance
    • Understand Access Requirements and Policies
    • Understand Security Requirements
    • Understand Entity Relationship Requirements
  • APPLYING QUALITY CONTROL TO DATA
    • Describe Characteristics, Rules, and Metrics of Data Quality
    • Identify Reasons to Quality Check Data and Methods of Data Validation
  • EXPLAINING MASTER DATA MANAGEMENT CONCEPTS
    • Explain the Basics of Master Data Management
    • Describe Master Data Management Processes