78 posts tagged qliksense, newest first.
For some time I have been thinking about how to improve the Sense development process as a whole. There is a lot of gathered experience and best practices from the wider software development community, but how can we apply this to Qlik Sense development? Some initiatives are starting to appear.
In a large Qlik Sense installations you are likely faced with a high number of reloads every hour. But some apps are more important than others – those apps should reload immediately when triggered. The alternative is that those important apps end up being queued after ongoing long running tasks – not
Such a simple thing – but oh how useful. One of the recent versions (3.0? 3.1? 3.1.1?) of Sense added much improved syntax color coding of the load scripts, as well as autocompletion of function names, field names, variables etc. What might seem like a small change
A summer project is over, and Butler has been released in a version that is a total rewrite of Butler version 1.x. Butler 2.0 includes features such as * Real-time monitoring of what users are active on a Sense Enterprise system * Real-time monitoring of failed reload tasks,
Long overdue, but during last few months I have finally started to play around with the various APIs available on the Qlik Sense platform. It has been said before, but it is worth repeating: those APIs are really, really powerful. They are one of the main reasons why I think
I recently investigated a strange behaviour of the Qlik Sense REST connector, where it would become slower and slower executing REST queries, the longer the server had been running. RAM or CPU consumption was not unusually high, but something was clearly eating away some kind of resources from the system.
The goal of the previously described Slack proxy project was to allow posting of messages from Qlik Sense load scripts to Slack (great instant messaging platform!). The project has however developed into something larger and slightly more ambitious, integrating other connections than Slack. The original project name “Slack proxy” has
With so much cool data available online, tools like QlikView and Sense becomes real Swiss Army knives of data integration. Pull in some data from company internal databases, some data from previously created QVDs, and more and more commonly also from various online sources, both public and private. Depending on
Quick update to the previous post on this topic. There is a new version of slack_proxy available on GitHub. It adds a new endpoint for creating directories on the server where slack_proxy is running. This obviously means that the apps name – “slack_proxy” – is not really that relevant
Real data and test data – both are needed One of the great things about both QlikView (QV) and Qlik Sense is their integrations with other systems. Given the native connectivity to any ODBC source, web pages in general, Salesforce, REST APIs, BigQuery etc – combined with the dozens of connectors provided
As the first version of the Sense-to-Slack integration required you to lower the Sense security level, it is probably not a good option for enterprise Sense users, for example. Instead, let’s set up a small node.js web service, which exposes an API that we can call
When thinking about it, it’s kind of strange that Slack has been so enormously successful. Sure, it’s a great instant messaging tool, but it’s not a new concept – IM tools have been around for decades, and IRC, Google chat and others rose to be very dominant and