data-visualization
🤟 Cevi Herdian -> itsmecevi.github.io
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📉 Technical Spesifications
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📘Curriculum Planning
🧗Pretest-Data Visualization
Introduction to Data Visualization-Asyn:
- The Power of Data Visualization:
- Hans Rosling
- Gapminder
- Goals :
- Data Exploration — find the unknown (trends, outliers, patterns)
- Data Analysis — check hypotheses
- Presentation — communicate and disseminate (share function-> data journalism)
- Confirmatory Analysis - to confirm our understanding and analysis of the data
- Information Design (Intro)
- Visualization Basics
- Colorology
- Simple Graphing Process:
- Workflow type 1 (we don’t have data): outcome->design->data searching-> data connection->Tableau (software)
- Workflow type 2 (we have data): data searching-> data connection->data preparation->sheet->[dashboard]->story
- Use Case Effective Charts
Essential Data Visualization Workflow & Techniques (Best Practices with Tableau)-Asyn+Syn
- Essentials Techniques:
- Tableau 101
- Tableau Business Intelligence Trends
-
Connecting to data:
- Live connection :
- When you have a fast database
- When you need up-to-the minute data (real-time)
- Extract connection (in memory) :
- When your database is too slow for interactive analytics
- When you need to take load off a transactional database (size of the data)
- When you need to be offline (without internet connections)
-
Data sources:
-
Data Preparation:
- Data connections :
- Union (vertical connection) : amazn_stock.pdf
- Joins / Blend / Inner Join (horizontal connection) :
- Left Join, Right Join, Full Outer Join
- Data Interpreter & Data Pivoting (Unpivoting) : CO2 API
-
Splitting : CO2 API Version-Indicator Name
- Manage data properties :
- Rename a data field:
- Assign an alias to a data value
- Assign a geographic role to a data field
- Change data type for a data field (number, date, string, boolean, etc.)
- Understanding Tableau Concepts: Data Global-Superstore
- Show Me Tool Bar
- Dimensions and measures
- Column & Rows Shelf
- Marks Cards
- Discrete and Continuous Fields :
- Blue color: discret, qualitative data (string, geographics, date, date & time, boolean). If added qualitative data, then they are separate the graphs.
- Green color: continuous, quantitative data, number, aggregation (sum, avg, etc).-> If added quantitative data, then they aren’t separate the graphs.
-
Hands-on chart: Tableau Visual-> hands-on chart.twb + Data-> Global-Superstore
- 1-Word maps: country, profit
- 2-Line chart: profit by category, profit by market, profit trendline, profit forecasting
- 3-Bar chart: profit, profit by ship mode
- 4-Bubble chart: profit by city
- 5-Tree maps: profit by region and subcategory, profit clustering, profit by product
- 6-Funnel chart: profit by segment
- 7-Waterfall chart: profit by sub-category
- 8-Pie chart: shipping cost by region
- 9-Maps: profit by state
- Aggregation / Calculation: When to use calculations,
- To segment data
- To convert the data type of a field, such as converting a string to a date.
- To aggregate data
- To filter results
- To calculate ratios
-
Hands-on calculation: Calculation
1. totals
2. percentages
3. profit ratio
4. diskon ratio
5. cost
6. aov (average order value)
7. profit status-if
8. profit level-elseif
- Machine Learning: Quick Clusterisation & Forecasting
- Sheet
- Dashboard (Filter, Actions Highlight, & Formatting)
- KPI-Sync: Thesis
- Business KPI
- Financial KPI
- Sales KPI
- Marketing KPI
- Project Management KPI
Project-Syn