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Our Leigh Kennedy, Distinguished Principal Enterprise Architect, is back with an updated look on applying software development life cycle (SDLC) concepts to your Qlik Cloud Analytics tenants. Take it away Leigh!


The majority of customers use some form of software development lifecycle in their organizations. When moving to SaaS customers are sometimes unsure of if or how to apply these techniques to a Qlik Cloud Analytics tenant.

We will explore some of the technical processes that need to occur within or interacting with a Qlik Cloud Analytics tenant as part of a software development lifecycle. We look at a number of areas including setting up your tenant in a way that supports your SDLC, encouraging re-use, building context aware applications, and many other topics. Qlik Cloud Analytics runs on Qlik Cloud, Qlik’s SaaS platform for our customer’s data analytics and data integration needs. We see customers being able to manage their entire data landscape and are continually expanding our cloud offerings. We have introduced new services such as Data Integration, Application Automation, Machine learning and AI, as well as adding many new features to Qlik Cloud Analytics. While there are many other areas where Qlik Cloud can be integrated into your SDLC, this document will focus on Qlik Cloud Analytics.

The aim of this document is not to provide a strict SDLC process for customers to follow, rather it aims to provide examples of how SDLC processes could work in a Qlik Sense Enterprise SaaS environment. We encourage you to implement or amend the parts or this you need so Qlik Sense Enterprise SaaS fits into your organization.

Read it all in the PDF attached in this post.

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