In the past few posts, I have discussed the modern, lightweight framework from Qlik, Nebula.js, and its usage in developing various Qlik Sense objects such as — creating a new visualization chart or building Embedded analytics solutions like Mashups. Nebula.js is a collection of product and framework agnostic JavaScript libraries and APIs that helps developers easily integrate out-of-the-box capabilities on top of the Qlik Associative Engine. So, let’s assume you have an already existing extension developed using the Extension API, and you would like to migrate this extension to the Nebula.js framework. How would you do this?

The focus of…

Modern Embedded Analytics solutions using Qlik offers a stack of open-source libraries to build customized analytical platforms backed up with the robustness of Qlik’s Associative Engine. These new mediums facilitates communication with the Engine and provides the flexibility to develop your own client and services or to integrate visualizations and mashups. Historically, Capability APIs have been extensively used to build mashups and perform application related operations. An alternative offering to Capability API-based operations is Nebula.js and Enigma.js.

To clarify the use of each of these libraries, let’s breakdown their functionalities in a simplistic way to help the developer community to…

Parallel Coordinate Plot(PCP) with Iris dataset.

In my last post, I discussed the robust capabilities of Qlik Sense(QS) APIs to build out-of-the-box visual metaphors and ways to integrate them within Qlik’s ecosystem. A natural choice for developers while building QS extensions throughout the years has been the ‘Extension API’ primarily using vanilla JavaScript, jQuery and AngularJS.

The Extension API consists of methods and properties used to create custom visualization extensions.

Enter… Qlik Sense’s Open Source Solution — Nebula.js!

Qlik Sense API’s have been a powerful set of tools for the developer community to build out-of-the-box capabilities and to integrate them seamlessly within the Qlik’s ecosystem. These APIs enable a developer to communicate with the Qlik platform using technology frameworks such as JavaScript, .NET to build custom Visualizations, widgets, or Mashups(integrating Qlik objects with web portal).

Consider a scenario where a customer already uses the benefits of Qlik Sense native charts and objects and their new requirement is to present some data in a chart that perfectly syncs with their use case but is not available within Qlik Sense…

AutoML is the medium of automating Machine learning pipelines to real-world problem through the use of an interactive platform to target some of the important processes like -

  1. Automated data preparation
  2. Automated feature engineering
  3. Automated Model selection
  4. Hyper-parameter tuning
  5. Quality evaluation

As part of my last Academic project, I had the opportunity to work on an intuitive platform to implement an AutoML kind-of interface to automate few of the processes, specifically —

  1. Ability to allow users to select a classification model.
  2. Hyper-parameter tuning
  3. Ability to play with interactive Visualizations.
  4. Ability to evaluate the classifiers using on-the-fly generated charts.

The intuition…

Dipankar Mazumdar

I am an R&D Advocate at Qlik where I experiment with the Engine. Also, a Visual Analytics Researcher at Dalhousie University.

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