Everything You Need to Know About Qlik Staige

In September this year, Qlik published the announcement of Qlik Staige. In Qlik's own words, a “holistic set of solutions to let Qlik customers embrace the power of Artificial Intelligence and deliver value”. A nice promise, but what exactly is Staige? In this blog, senior consultant Lennaert van den Brink explains it to you.

Not a new product

Unlike, for example, the Business Glossary or Qlik Data Integration, Staige isn't a new product or a new feature you can use in Qlik. Instead, Staige is actually an umbrella term for all the features in Qlik that make use of artificial intelligence (AI) in one way or another. Think of the Insight Advisor or AutoML, but also, for example, connectors with OpenAI or Amazon Sagemaker.

Besides serving as an umbrella for all AI-related features, Staige is also a vehicle for Qlik to spread their vision on AI and Machine Learning. On the Staige site you'll find a series of articles in which Qlik describes how they view the trends in this field.

Qlik's vision in short

You're of course very welcome to read Qlik's own articles, but in short it comes down to this:

Artificial Intelligence is going to play a big role in (business) life in the near future. Companies that don't use these technologies will lose out to companies that do. Nevertheless, many companies find it difficult to already get value out of these new technologies. Many companies jump on this trend by promising new products and applications that use AI. Qlik has already incorporated many of these technologies into its products over the past few years and is therefore strongly positioned to support customers through this transformation. In doing so, Qlik focuses on three activities:

1. Developing a reliable data foundation: the basis of AI is quality, relevant, and available data. Data is needed to train the models in order to apply them. On top of that, the risks around data are growing, for example in the area of privacy sensitivity or competitive advantage over rivals. It's therefore essential to lay a solid foundation on which you can build the various AI applications. With solutions such as Talend, QDI, and Data Catalog, Qlik has a strong set of tools in house to build this foundation.
2. Find insights and act immediately with AI-powered analytics: Back in 2021, Qlik already spoke about Active Intelligence. With the term Active Intelligence, Qlik means that data is continuously put to work to fuel actions and decisions. An important feature here is Application Automation, which lets you chain different activities together. For example, with Application Automation you can immediately run an AutoML prediction model on new data in a customer database, after which a sales manager is prompted with a specific action based on the result. In addition, using the Insight Advisor and AI-generated load scripts, expressions, and visualizations, you can easily and quickly explore, transform, and visualize your data to arrive at new insights, without needing deep expertise.
3. Build and implement AI for advanced use cases: With AutoML, Qlik makes advanced prediction models accessible to a larger group of users and enables existing specialists to develop new prediction models even faster. Because AutoML is fully integrated into the Qlik Platform, the new models can be rolled out to production environments quickly and easily so they can add value right away.

Written by Lennaert van den Brink
Senior Consultant