"Visualisation and analytics tools apa yang ada kat market sekarang?"

First, tengok focus ke arah mana, either analytics or visualization. Second, tengok specialisation tu ke arah data type or a particular domain.

Thread of 15 visualisation and analytics tools.

Open Source Visualization Frameworks and Libraries

1. Plotting in R: ggplot2

Link: http://ggplot2.org 

Kegunaan: Sesuai untuk draw static plot and graph. Apa itu static plot and graph? Kita bincang kat thread lain.

Documentation lanjut boleh refer: http://docs.ggplot2.org/ 

2. Interactive web applications for R: R Shiny

Link: http://shiny.rstudio.com 

Kegunaan: Sesuai untuk plot interactive plot dan untuk lagi advanced boleh buat full functioning dashboard.

Boleh refer tutorial di sini: https://shiny.rstudio.com/tutorial/ 

3. Static Python plotting library: Matplotlib

Link: http://matplotlib.org 

Kegunaan: Sesuai untuk draw static plots and graphs. Yang bestnya boleh combine with interactive HTML widgets. Refer: https://github.com/ipython/ipywidgets

Also Seaborn extension. http://seaborn.pydata.org/ 

4. Another programming language and IDE: Processing

Link: http://processing.org 

Kegunaan: Instant visual feedback and cross-platform. Best sebab boleh guna HTML5 Canvas and WebGL for rendering.

Tutorial boleh refer: https://processing.org/tutorials/ 

5. Data-driven document: d3js

Link: http://d3js.org 

Kegunaan: Free Java Script library and very popular.

Boleh tengok example best di: https://beta.observablehq.com/@mbostock/d3-bar-chart

6. A Visualization Grammar: VEGA

Link: http://vega.github.io/vega/ 

Kegunaan: Declarative language for creating, saving, and sharing interactive visualization designs.

Boleh refer contoh bar chart disini: https://vega.github.io/editor/#/examples/vega/bar-chart

7. Something similar to jupyter notebook: Observable

Link: https://beta.observablehq.com/ 

Kegunaan: Full D3.js & VEGA integration. True interaction (not just with predefined Python widgets).

Boleh explore samples di: https://observablehq.com/explore 

8. Declarative statistical visualization library for Python: Altair

Link: http://altair-viz.github.io/ 

Kegunaan: Declarative statistical visualization library for Python and based on Vega and Vega-Lite. User selections can be fed back into notebook.

9. Declarative charting library: Plotly

Link: http://plot.ly 

Kegunaan: Semua jenis charts ada. Ada juga plotly.js: Built on top of d3.js. Also available for Python, R, Matlab

Yang berbayar

10. Business Analytics Software: Tableau

Link: http://tableau.com 

Founded in 2003, ~3500 employees. Co-Founder: Pat Hanrahan from Stanford. Recently introduced Tableau Prep

11. Data visualization & analytics software: Spotfire

Link: http://spotfire.tibco.com 

Emerged from research software @ Univ. of Maryland. Acquired by TIBCO in 2007.

12. Business analytics software: Power BI

Link: http://powerbi.microsoft.com 

Ini paling aku banyak guna sekarang and ok untuk fulfill kehendak industry. Banyak thread aku akan focus on Power BI lepas ni ok?

13. Another business analytics software: IBM Watson Analytics

Link: http://www.ibm.com/analytics/watson-analytics

Recently replaced by IBM Cognos Analytics. Boleh tengok promotional videos dia di sini: https://www.youtube.com/user/watsonanalytics

14. Data wrangling tool: Trifacta

Link: http://trifacta.com 

Kegunaan: Best sebab dia boleh presents automated visual representations of data based upon its content. Also Perform data transformations.

Short promotional video: https://www.trifacta.com/resource/trifacta-wrangler-demo/

15. Open Source Java-based graph vis and analysis tool: Cytospace.

Link: http://cytoscape.org 

Ini kepada siapa yang familiar with Java. Web-version: cytoscape.js

Aku terus tunjuk tools sebab boleh juga nak belajar asas visualisation and analytics terus dengan pakai tools.

Aku nak specifically tag @wolfipali, @arif_jamaludin_, @amirulhakiim_ , @nfzaali and @imranhakmm, sebab ada tunjuk interest ini analytics area.

Sebarkan.