Read: DESIGN by data course outline

Course abstract

Parametric, digital design, building information modeling and many of this technology is base on the basic of data.

1. we want to understand how data is being managed
2. learn to create a story base on data
3. design optimization

Data Visualization is a big part of a data designer scientist’s jobs. In the early stages of a project, you’ll often be doing an Exploratory Data Analysis (EDA) to gain some insights into your data. Creating visualizations really helps make things clearer and easier to understand, especially with larger, high dimensional datasets. Towards the end of your project, it’s important to be able to present your final results in a clear, concise, and compelling manner that your audience, whom are often non-technical clients, can understand.

Introduction

1. Business Intelligence- introduction

Business intelligence is a technology driven process for analyzing data and presenting actionable information to help corporate executives, business manager and other end users make more information business decisions.

1. Improves the decision making process
2. Helps you know your business
3. Reduces the risk of bottlenects
4. Help indenify waste in the system
5. Enable real time analysis with quick navigation
6. Make it easy to access and share information
7. Benifits of BI
8. Different BI tools- (en.wikipedia.org/wiki/Business_intelligence_tools)
9. Why Tableau? What is in for me?
10. Tableau- Intoduction and product suite
    • For development of dashboards:
    • Tableau Server
    • Tableau Online (Hosted Tableau Server)
    • Tableau Reader
    • For Learning- Tableau Public- Free (no local files, public publishing only, can connect to limited data sources…)
11. Obtaining and installing tableau- Search Tableau Public
12. Excel Vs tableau
13. Getting started
14. Gretting your data into tableau
15. The Tableau Workspace
16. Creating your first visualization
    1. Data pane
       • Current data courses are listed at the top of the data pane
       • Below the data sources the fields available in the currently selected dtat sources are listed
       • You can search for fields in the data pane by clicking the magnifying class icon and then typing in the text box
       • Click the view data icon at the top of the data pane to see the underlying data.
       • The data pane is organized into several areas:
       • Dimensions- fields that contain category data such as text and dates
       • Measures – fields that contain numbers that can be aggregated
       • Sets subsets of data that you define
       • Parameters dynamic placeholders that can replace constant values in calculated fields and filters

1. Visualization Analytics- introduction
   • Visual analytic is a form of inquiry in which data provides inslight into soloving a problem is displayed in an informative, graphical manner
   • It helps identfy trends, patterns and relationships in the data.
   • Visual analytics is es
2. Creating Basic charts- Pie, bar, line, scatter, etc
3. Creating advanced chart- geosptial maps, dual axis charts, multidimensional
4. Visualization, Gantt charts, etc
5. Data management- filters, sorting grouping, Hiearchies, joining, blending, time dimensions,, etc
6. Data manipulation- calculation fields, table calculations, parameters,
7. Subsets, level of details, aggreatation concepts, context filters, etc
8. Advance analysis- concepts of predictive modeling, regression, time series, building predictive models, using tableau, integrating tableau with R, etc
9. Presnting your work- dashboards, stories, publishing your work to tableau servers, user level security, scheduling refresh, etc
10. Project assisgnment