Systems | Development | Analytics | API | Testing

Systems development lifecycle (SDLC) with the Qlik Active Intelligence Platform - Part 2

In this video we will show how we can build context-aware applications so, your applications will know not just whether they are in Development, Test or production, but also whether they are a Sales, Finance or HR app. We will do this using built-in functionality of Qlik Cloud. We will also look at using these techniques to manage external script libraries so we can ensure we use the correct version of libraries based on where our apps reside.

Modernizing the Analytics Data Pipeline

Enterprises run on a steady flow of best-fit data analytics. Robust processes ensure these assets are always accurate, relevant, and fit for purpose. Increasingly, organizations are implementing these processes within structured development and operationalization “pipelines.” Typically, analytics data pipelines include data engineering functions such as extract-transform-load (ETL) and data science processes such as machine-learning model development.