Qlik Customer Day 2023: your questions answered

1. Are there plans to offer network (concurrent) licenses in the future?

Besides previous licensing models with named user licensing and Analyzer Capacity is purchased in packs of 1000 minutes/month, Qlik has added Qlik Cloud Data Pack licensing based on data analyzed which offers unlimited Analyzer users.

2. Can Qlik extensions work on Qlik Cloud?

Yes, you can manage extensions using Qlik Cloud Administration. Read more here>

3. What is the migration process to Qlik Sense Cloud? Does it mean rebuilding all dashboards and data models?

Qlik Sense apps can be distributed directly to the Cloud without re-building…However, in the migration process, we do see customers take the opportunity to “clean up” their app environment which means some rebuilding, but this is optional.

4. Can Qlik Sense Cloud backup to non-cloud storage, like a local NAS?

No it cannot at this time.

5. Are there any limitations of Qlik Cloud that should be considered when moving from Qlik Sense on-premises?

Qlik partner should do evaluation of current application size, as depending on Qlik Cloud subscription model, without extra fee, app sizes can be 5 GB or 10 GB. It is possible to have also a larger application for additional fees.

6. For on-premises, any plans to have a built-in deployment pipeline for DEV-PROD application metadata cross-checking? Also, ETL lineage view as in the cloud?

For on-premises (client managed) installation customers can access ETL analysis trough hybrid solution and have lineage through Qlik Cloud Analytics. To explore these features, we can provide 1-2 trial licenses for our cloud services. Please contact us to arrange these trials.

1. Will the cloud offer a folder structure for extracted QVD files?

Qlik is working on developing folder structure, plans Q4 2023 – Q1 2024.

2. How can you get your data from Qlik Cloud if you cannot pay for services? CSV, QVD, or is it impossible?

From Qlik QVD files you can write data into CSV and parquet file formats with Qlik Cloud automation use even more capabilities. Read more here>

3. What are the top three channels (website, YouTube, etc.) to follow for Qlik news, best practices, and other information?

• Qlik Community
• Qlik Resources
• Riga Qlik Meetup
• Vilnius Qlik Meetup
• Infotrust Youtube channel

AutoML is available in Qlik Cloud, but it can be easily combined with Hybrid approach. On-premises many customer using Qlik Advanced Analytics integration, i.e., with R and Phyton predictive models, bringing predicted values back to Qlik applications.

2. Will AutoML work on-premises?

No, as it requires significant hardware resources. Easiest option is to go with Hybrid scenario, linking Qlik Cloud to client managed Qlik Sense Enterprise.

3. Does Qlik AI work only with English-labeled data? What company is using Lithuanian-only labels and values on dimensions and measures?

AI can work with any language, as mainly it is about the data from which the AutoML can build predictions, labels are for humans to understand.

4.How do you see your main downside from a user perspective, and how are you addressing it? Also, what would you consider your top advantages?

One downside from a user perspective is that downloading data files directly from the Qlik catalog isn’t as streamlined as it could be; however, we’re actively working on enhancements to this feature.

On the other hand, our top advantage is the Qlik Cloud’s ease of use and associative difference, which allows users to explore data intuitively by revealing how data points are interrelated. Unlike linear exploration in other BI tools, Qlik’s associative model illuminates hidden trends and patterns by connecting all data points across multiple sources, making data discovery easy and comprehensive for users of all skill levels. This intuitive approach sets Qlik apart and empowers users to make informed decisions based on a full spectrum of their data.

1. If my organization can’t use cloud services because of safety reasons, can we still use the full capabilities of the AI?

Qlik Sense does utilize AI capabilities that are built into the engine. The only feature that is not available on premise is AutoML.

For client managed (on premise) customers also can leverage Qlik Adavanced Analytics integretation – read here.

2. Is Staige already available for use, and will it be integrated into Qlik Sense Cloud?

Qlik Staige is more of a set of features that we do have already in the Cloud, it’s a set of best practices to take advantage of AI within Qlik Cloud.

3. Does real-time data impact the speed of ERP operations? Are there any disadvantages or challenges associated with using real-time data?

Using CDC (change data capture), real-time data typically has minimal direct impact on ERP operations speed. This is because CDC is designed to non-intrusively capture and propagate data changes from source systems in real-time or near-real-time.

4. When will the Qlik Reporting Service (SaaS) start distributing reports in XLSX format?

It will be released, current status is “in development”, this Qlik App provides a summary of all ideas and their status – read here>

5. Will this custom dashboard-making tools be available to end customers, or are they exclusively for developers? Are they available now?

End customers can use built-in Qlik mashup functionality.

6. Can you provide more information on how ML predicted values data is handled? Is it fetched on-the-fly (cached), or can it be appended to the dataset?

It can do both!

7. What are the strategies or tactics companies can employ to formalize AI, and what is the most powerful practical application of AI for companies at present?

Companies can adopt strategies such as initiating pilot projects with tools like Qlik AutoML to demonstrate quick wins. It simplifies the creation of machine learning models, enabling organizations to forecast trends and make data-driven decisions efficiently.

Additionally, companies can leverage Qlik’s advanced analytics integration capabilities, which allow for the use of open-source languages like R and Python. This enables the enhancement of Qlik’s analytics with sophisticated, custom-built models and algorithms, offering greater flexibility in data analysis.

1. Are there any plans for on-premises users to make the analysis and manipulation of QVD data files easier, such as a PowerQuery editor?

Yes! This is in development now.

2. Can you tell a bit more on how ML predicted values data is handled? Is it fetched on-the-fly (cached), or it could be appended to the dataset?

Both!

3. What is the tool that can effectively consolidate data connections and sources from multiple apps into a unified schema?

I believe this can be done when we release the file-structure inside of the data catalog.