Lesson 1: Data Visualization Fundamentals\ 1. Visualization definitions: standard ones and your interpretations\ 2. Data visualization usage/benefits\ \ Lesson 2: Data and Visual Structure: (IMPORTANT)\ 1. Identify variables and observations in a given dataset\ 2. Scales and measurements: nominal, ordinal, interval, ratio\ a. Definition\ b. Examples\ c. Interpretations\ Nominal & ordinal= categorical\ Interval & Ratio= quantitative\ 3. Categorical vs. quantitative\ 4. Discrete vs. continuous\ 5. Time factor: cross-sectional vs. time-series: Just know the differences\ 6. Visual decomposition: name and nature of structural variables\ \ Lesson 3: Design Principles\ 1. Be able to critique a visual\ 2. Design principle: expressiveness and effectiveness\ 3. Understand colors: categorical vs. quantitative use\ \ Lesson 4: Business Intelligence Models\ 1. Data mining: definitions\ 2. Core ideas in data mining\ 3. Supervised learning\ 4. Unsupervised learning\ 5. Supervised example: decision tree\ a. Definition\ b. General interpretations\ 6. Supervised example: Neural nets\ a. Definition\ b. General interpretations\ 7. Unsupervised example: cluster analysis\ a. Definition\ b. General interpretations\ \ Lesson 5: Chart Types\ 1. Cross-sectional vs. time-series vs. longitudinal\ a. Definition\ b. Example\ c. Interpretations\ 2. Categorical examples: bar chart; clustered bar chart; waterfall...\ a. Definition\ b. Example\ c. Interpretations\ 3. Hierarchical: pie chart (donut chart); (100%) stacked bar chart; tree map...\ a. Definition\ b. Example\ c. Interpretations\ 4. Relational: scatter plot; bubble chart...\ a. Definition\ b. Example\ c. Interpretations\ 5. Temporal: line chart; dual axis chart...\ a. Definition\ b. Example\ c. Interpretations\ 6. Spatial: maps\ \ Lesson 6: Data Modeling Basics\ 1. Logical keys: primary vs. foreign keys\ a. Definition\ b. Example\ c. Interpretations\ 2. Main data types\ 3. Three database relationships\ 4. Understand the definition and usage of a bridge table in a data model\ 5. Differences between a star schema and a snowflake schema\ 6. Understand cross-filtering in Power BI: directions\ 7. Differences between Single-Cross-Filtering and Both-Cross-Filtering\ 8. Understand Join and Union in Tableau: examples and interpretations\ a. Left join\ b. Right join\ c. Inner join\ d. Full outer join\ e. Union