The News: On June 4th and 5th, Qlik, the AI and data integration, quality, and analytics company, held its annual Qlik Connect conference in Orlando, Florida. Among other announcements, Qlik introduced the Qlik Talend® Cloud and Qlik Answers™, featuring integrated AI capabilities. For more information, see the press release on the Qlik website.
AI in Context: Qlik Connects Data Analytics to AI
Analyst Take: Although data analytics was a popular topic in the computer industry 10 years ago, the resurgence of AI and its integration with related technologies has pushed analytics down the stack and, sometimes, to the back of people’s minds. It is still here and more important than ever as the amount of data we generate and must curate to get valuable insights has exploded. Qlik continues expanding its offerings and introducing AI into the platform. Not to be forgotten in the frenzy around Generative AI, Qlik continues maturing its predictive AI features and ensuring that its customers have all the tools they need to maintain the highest data quality standards.
Remembering the Four Vs and Big Data
Ten to fifteen years ago, when AI was in early spring after one of its winters, big data, analytics, and operations management were the buzz. We spoke about the “Four Vs”:
- Volume: the ever-increasing amount of data. For Generative AI, we see this in models trained on billions to trillions of tokens.
- Variety: the format and kinds of data. We have structured, semi-structured, and unstructured data, but also text, numbers, images, video, audio, enterprise data, and scientific measurements, for example.
- Velocity: the speed of new data creation and the different ways we generate it. In 2021, the World Economic Forum estimated that we created 500 million tweets, 294 billion emails, and 4 million gigabytes of Facebook data. We must also include all the other social media data, articles, books, images, videos, films, music, and, of course, Futurum Group Research Notes such as this.
- Veracity: the trustworthiness and correctness of the data.
Some categorizations replaced Veracity with Visualization. One of Qlik’s first products was data visualization.
Regarding veracity, the phrase “garbage in, garbage out” goes back to the 1950s and the early uses of computers. If you are performing a calculation and the input numbers are wrong, there is no reason to expect the answer to be correct. Perhaps someone copied the values incorrectly, or some measurement device was poorly calibrated.
Numbers are data, and we can extend this concept to information in general. If you train a Generative AI LLM on misinformation, the text it creates will generally be wrong unless some later process, such as Retrieval Augmented Generation (RAG), corrects it. Therefore, it is paramount to start with the best data possible and have a single source of truth for it.
AI has now absorbed data analytics and data science, though we still consider them subfields and disciplines. While focusing on the AI use cases, we must not forget the underlying data management infrastructure, with analytics and visualization. This is what Qlik does well, as in its Qlik Sense product.
Qlik Sense is the modern incarnation of the company’s first product from 1994 and features data loading, analytics, visualization, dashboard creation, reporting, data alerting, and general Business Intelligence (BI) functions.
Qlik Provides Answers
Given all this data, how do we make sense of it beyond the numbers, the graphs, and the charts? If only there were some way to take your business data, computed analytics, and a compendium of knowledge and express answers to user queries in straightforward language.
The company introduced its new Qlik Answers product at the conference. Qlik terms it a “generative, AI-powered knowledge assistant” that lives on top of your data and reflects the information quality in which you have invested. Starting with a core foundational model and layering your varied data on top, Qlik Answers generates text and explains relationships that tell you more about your business than you might otherwise be able to glean. As a self-service offering, you can use the generated information to justify actions, develop strategy, adjust tactics, and better understand what you are doing and why. As you further augment your data infrastructure with other Qlik products, Qlik Answers will provide better and more complete responses to your prompts.
I like Qlik Answers because it is a natural companion to what you already have. While Generative AI responses can be strange because of poor data quality and hallucinations, you can control the veracity of your organization’s inputs.
That’s Cloud, Not Qloud
Qlik acquired Talend in 2023, adding features such as data integration and governance to the company’s portfolio. At the conference, Qlik executives noted that the post-acquisition integration is complete. Moreover, the customer overlap between the two companies was only 10%, so the opportunity for cross-selling was and is an important business driver. Qlik will continue to use Talend as a brand as long as it has customer recognition beyond the portfolio.
The newly announced Qlik Talend Cloud firmly shifts the introduction of new Qlik features in the direction of the cloud. The platform features more extensive drag-and-drop tools for the no-code data management lifecycle.
Qlik has a deep focus on data quality and governance. Where did it come from? How did it evolve? Can I trace its lineage? This is one of the many features in the Qlik Talend Cloud, along with real-time data movement and transformation.
While data and its processing, for AI or any other reason, can be done on-premise, on the cloud, or a hybrid of both, many vendors are choosing to introduce new features on the cloud first. Qlik understands that users want to decide what is done where, given financial, security, and legacy considerations. This is a big part of the richness of the Qlik platform. Keep an eye on the Qlik Talend Cloud and where Qlik takes it. Base your data strategy on consultations with their experts. If you have a heterogeneous data platform, and many people do, work with Qlik and its partners to create the best architecture for your needs.
Prescriptive and Generative AI
During the conference, I posted this on LinkedIn:
Don’t let the current generative AI obsession make you forget predictive and prescriptive AI and data analysis. Sucking in massive amounts of text and media and then spitting out a generated answer is not a replacement for optimization and computation.
Predictive analytics or AI uses a model based on existing data and a lot of math to guess with a high degree of confidence about what might happen in the future. “What will my sales likely be in July based on historical results?”
Prescriptive analytics or AI also uses data, a model, and a lot of math, but it computes an optimal course of action to achieve some goal. “What should I do to maximize sales in July?”
While we might use Generative AI tools to understand the questions being asked, it is silly to assume that the answers to such queries lie somewhere in the training data. That is, Generative AI does not equal AI. Sure, it’s an important and remarkable tool, but it is one of many.
When I ask a question of a system or enter a prompt, I want the best answer, whatever the AI techniques used. Qlik understands this and has built a solid global business based on traditional analytics. It increasingly uses Generative AI to enhance access to these capabilities and their output.
Key Takeaway
Qlik continues to flesh out and fill gaps in its portfolio via its integration of Talend and new products, which seamlessly incorporate Generative AI.
Qlik has an impressive set of offerings. Their community is quite familiar with the product details and recognizes and appreciates the new features announced at Qlik Connect. I have two recommendations for the company:
- Bring the descriptions of the many products and tools up a level to reduce the density of the list and the technical use cases.
- Consider more targeted marketing campaigns based on parts of the platform and the company’s culture of sustainability and supporting charities.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold an equity position in any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other Insights from The Futurum Group:
At AI Field Day, Qlik Shows AI-Based Analysis Added to Its Platform
The Evolution of Low-Code/No-Code Platforms
The Futurum Group with Qlik at AWS re:Invent 2023 – Futurum Tech Webcast
Author Information
Dr. Bob Sutor has been a technical leader and executive in the IT industry for over 40 years. Bob’s industry role is to advance quantum and AI technologies by building strong business, partner, technical, and educational ecosystems. The singular goal is to evolve quantum and AI to help solve some of the critical computational problems facing society today. Bob is widely quoted in the press, delivers conference keynotes, and works with industry analysts and investors to accelerate understanding and adoption of quantum technologies. Bob is the Vice President and Practice Lead for Emerging Technologies at The Futurum Group. He helps clients understand sophisticated technologies in order to make the best use of them for success in their organizations and industries. He is also an Adjunct Professor in the Department of Computer Science and Engineering at the University at Buffalo, New York, USA. More than two decades of Bob’s career were spent in IBM Research in New York. During his time there, he worked on or led efforts in symbolic mathematical computation, optimization, AI, blockchain, and quantum computing. He was also an executive on the software side of the IBM business in areas including middleware, software on Linux, mobile, open source, and emerging industry standards. He was the Vice President of Corporate Development and, later, Chief Quantum Advocate, at Infleqtion, a quantum computing and quantum sensing company based in Boulder, Colorado USA. Bob is a theoretical mathematician by training, has a Ph.D. from Princeton University, and an undergraduate degree from Harvard College.
He’s the author of a book about quantum computing called Dancing with Qubits, which was published in 2019, with the Second Edition released in March 2024. He is also the author of the 2021 book Dancing with Python, an introduction to Python coding for classical and quantum computing. Areas in which he’s worked: quantum computing, AI, blockchain, mathematics and mathematical software, Linux, open source, standards management, product management and marketing, computer algebra, and web standards.
