Analytics with D3.js in Drupal 8
What is Analytics?
Analytics is the art of discovery, interpret, communicate and represent the data in various patterns. Analytics often favours data visualization to communicate insights.
Types of Analytics?
- Customer Intelligence
- Marketing Analytics
- Web Analytics
- Social Media Analytics
How is analytics useful?
Analytics can be used to track past and current consumer behavior, to help determine priorities and hence predict user action in terms of content consumption, product sale etc. This means enhanced conversion rates and hence increased business. Analytics can be used to promote and propagate relevant content, products and service to highly targeted audience.
What is D3?
It is a framework which is helpful in representing data in HTML, SVG and CSS formats. Because of minimal overheads of any other js or external library, D3 is extremely fast and supports large data sets with dynamic interaction as well. This make it an obvious choice for building an analytics solution.
- D3 is very powerful tool for data visualization. Reason for its popularity is that it works flawlessly on web.
- Another reason of D3’s popularity is the raw output which we can be manipulated as any DOM object as per the user needs.
- D3 also handles default browser's functionality which reduces developer’s efforts, e.g. Mouse interaction etc.
- We can reduce the code redundancy. We can reuse the code and can add particular functions to the core
- No Browser dependency
- if used wisely, it is performance optimized
When to use D3.js?
- It should be used when webpage is interacting with the data.
- D3 means Data Driven Documents with Graphing Capabilities.
Why D3 with Drupal as backend?
- D3 provides rich UI visualization.
- D3 can integrated with Drupal at presentation and business layer
- Visualization built with using D3 and Drupal can be downloaded instead of presenting on web
- Headless implementation of Drupal 8 with D3.js as the front end and Drupal as the back end being used for data being ingested from multiple database sources; acts as an ideal and easy to use implementation for building an analytics solution.
- Drupal’s Content Management capabilities coupled with D3’s data visualization expertise presents an opportunity to create such an analytics solution
What we’ll discuss?
1. How can data analytics be useful in Drupal?
2. Which are the frameworks we can use for Data Analytics?
3. Why d3.js?
4. Architecture behind the d3.js
5. What are the important parameters for d3.js?