Latest news with #QlikConnect2025
Indian Express
21-05-2025
- Business
- Indian Express
From searching to answers: Qlik CTO explains how AI is reshaping data interaction
'If you look at the evolution of data, the earliest uses were basic. People captured data in spreadsheets and notes to make decisions. What has evolved are the techniques and organisational literacy around leveraging it,' said Sharad Kumar, CTO of Qlik, while describing the evolution of data. Data is no longer just columns and rows; it has moved on from being a unidimensional fact and figure to something more dynamic. Today, almost every aspect of our life is governed by data, and we have arrived at a point where data is enabling decision-making for organisations. On the sidelines of the recently held Qlik Connect 2025 in Orlando, caught up with Kumar, who shared his insights on how AI is shaping data integration and modern business strategy. During the conversation, Kumar outlined three major transformations in data analytics over the years. He shared that it all began with the centralisation phase with data warehousing. 'When we started building data warehouses like Teradata decades ago, it was the first transformational change. We focused on pulling data once, centralising it in one place, and making it easier for people to access. This gave us a backward view of data, which we call descriptive analytics'. The next phase was predictive analytics. Kumar revealed that this was the phase when machines were being trained and building machine learning algorithms on the same data. Later the world moved from a historical view to a forward-looking view that could predict outcomes for smarter decisions. 'Think about recommendation engines on Amazon or Netflix—that's machine learning in action.' According to Kumar, the recent transformation came with the generative AI wave. 'Suddenly having access to ChatGPT two years ago completely changed the landscape.' What fundamentally changed was how humans interacted with data. Now it's not about searching for information; it's about getting answers—a fundamental switch,' he explained, adding that the evolution continues at an accelerating pace. Kumar went on to state that the next wave is already here: agentic AI. With agentic AI, it is not about asking; Kumar feels that one can express their intent, and agents will determine which processes to deploy and in what sequence. 'Going from warehousing to predictive took a long time, but the transitions from predictive to generative and from generative to agentic are happening much faster. The pace of change is compressing,' Kumar said. As generative AI has become a buzzword across the spectrum, we asked Kumar what was hype and what was real when it came to its enterprise use cases. The Qlik executive acknowledged that while generative AI has captured the attention of the C-suite, its implementation hasn't been an easy one for many. Kumar also said that the ground realities are different. 'When you talk to data and AI practitioners, you find that the data is not ready. It's messy, siloed, low quality, not timely, and often can't be trusted. If you build AI systems on bad data, they will fail,' he said, adding that this was indicative of why success rates remain modest. 'Only about 25 per cent of AI projects are truly succeeding in delivering business value. The biggest challenge is the data foundation,' he said. When asked how the gap can be closed, Kumar recommended a two-pronged approach. 'Enterprises that are succeeding are starting with narrow AI use cases that are contained and less risky. At the same time, they're focusing on getting their data foundation right, which is the only way to scale AI effectively,' he said. On being asked how Qlik's platform supports the journey from raw data to business outcomes, Kumar explained that the platform offers a wholesome assistance to businesses through their data journeys. The executive said that the journey begins with data collection. 'First, we provide capabilities to get data from anywhere—databases, SaaS applications, complex systems like mainframe and SAP, files, and streams—at high velocity in near real-time.' Data collection is followed by integration. Kumar said that Qlik allows businesses to join and integrate siloed data. 'Unless you can join data together, you cannot get a complete picture. If customer information is in one system, purchases in another, and return information in a third, you need to connect these to understand your customer.' After integration, building trust in data follows. The company helps businesses by helping them assess data quality, preserving the lineage of data to trace their roots. Later, the Qlik platform enables multiple types of analytics. 'Once you have a trusted data foundation, you can build BI visualisation dashboards for descriptive analytics, machine learning models for predictive analytics, and conversational agents for generative AI,' he explained. Kumar added that finally Qlik enables action, as it allows customers to take insights and automate actions on them. When it came to challenges faced by enterprises in modernising their data, Kumar revealed that there are three primary challenges, such as data migration, skill gaps, and funding. Data migration is a challenge, as most data today, according to Kumar, continues to be in on-premise systems. Getting this data onto the cloud is a considerable challenge for many. On the other hand, with many organisations moving to cloud and AI, Kumar feels that most of them often lack the necessary skills, especially for AI implementation. Lastly, with funding, most companies think that they don't need much budget for AI, as ChatGPT gives the perception that you can quickly apply models. 'What we're finding is that you need a significant budget to fix your data foundation, which is a heavy lift,' he noted. When asked what his recommendations would be for organisations, Kumar said, 'Funding for data foundation should be rolled into their overall AI initiative funding. If you don't properly fund your data initiatives and have the right technology and the right skills, you'll face challenges.' Lastly, on being asked what excites him the most about the future of data and AI, the Qlik executive said that potential applications of AI to streamline data workflows are something that he looks forward to. More broadly, he sees AI transforming every aspect of business and daily life. Bijin Jose, an Assistant Editor at Indian Express Online in New Delhi, is a technology journalist with a portfolio spanning various prestigious publications. Starting as a citizen journalist with The Times of India in 2013, he transitioned through roles at India Today Digital and The Economic Times, before finding his niche at The Indian Express. With a BA in English from Maharaja Sayajirao University, Vadodara, and an MA in English Literature, Bijin's expertise extends from crime reporting to cultural features. With a keen interest in closely covering developments in artificial intelligence, Bijin provides nuanced perspectives on its implications for society and beyond. ... Read More
Indian Express
15-05-2025
- Business
- Indian Express
Why human oversight alone is not enough to safeguard AI, says global AI policy advisor
Artificial intelligence is moving at a brisk pace, and organisations around the world are scrambling to deploy the latest in AI to ensure they are not left out. If last year was all about generative AI, this year the conversations have moved on to agentic AI, or AI that can assist humans in automating specific tasks. There is no uniformity in the deployment of advanced AI among organisations of all sizes; this is perhaps owing to the absence of a global standard for scaling and deployment of AI in the enterprise segment. In times like this, credible voices and their views on the rapid developments in AI, gaps in execution, and challenges pertaining to governance need to be heard. Kelly Forbes, a member of the AI council at Qlik, firmly believes that as AI gets smarter, we need to get even smarter while working with AI. Forbes feels that corporate-led AI councils play a role in shaping best practices and ensuring compliance with regulations for the world to follow. On the sidelines of the Qlik Connect 2025 in Orlando, sat down with Forbes to understand the challenges faced by enterprises in the ever-evolving landscape of AI. Below are the excerpts from the conversation. Bijin: From the governance lens, what do you think enterprises are struggling with when it comes to scaling AI, despite having their defined strategies in place? Forbes: I think Mike (CEO of Qlik) has put it in the right way in saying that we currently have AI available, but actually the adoption implementation is very small. So we haven't reached the level that we need to be reaching. Part of that is because we do have a few AI constraints. Sometimes it's a deeper understanding of local policies or regulations data, or there might be issues around infrastructure. On a practical level for businesses, a lot of the time, I think it's just a lack of understanding how AI can support them within their local capacity. We are now finally at a stage where most companies can recognise the role the AI will play, and now they're figuring out what that actually means in 'my context, for my company and for the processes'. That is taking time. Bijin: For our readers, can you simplify what the AI Council is, and with reference to Qlik, what exactly is the AI Council? Forbes: The AI Council has brought four of us together with very different expertise and experiences to guide and support Qlik on this journey. AI is evolving quite fast, and governance needs to adapt to that. There are a lot of questions around governance, infrastructure, what the technology can do, and how you can best support businesses. What might be happening here in the US is different from what might be happening in India or in the Middle East. The AI Council has been able to show value and support in that interaction and journey. Bijin: During the keynote address, there was a distinction outlined between Gen AI and agentic AI. When we talk about agentic AI, what kind of safeguards or policy framework should be in place to ensure that these autonomous systems remain accountable? Forbes: Last year we were speaking about generative AI. This year we're speaking about agentic AI; probably next year we're going to be speaking about new developments. It's moving very fast. But safeguards remain the same. What we're seeing more with agentic AI is that we are seeing more autonomy given to AI. It requires less human input. The moment you do that, the machine will run on its own. We have to make sure that it's running well and not making mistakes, and how are we keeping it accountable? There are a lot of practical processes, and most of them we are implementing. Having a framework, having tools supporting businesses, and keeping ahead in terms of what those standards and foundations should look like. I had a meeting just today with a few of the colleagues from the team, and they were explaining everything they're doing around implementing different processes into their work to make sure that AI safeguards are evolving at the same time that AI is evolving. You had Gen AI and agentic AI, but your safeguards are currently being updated at the same time as well. Bijin: You (Qlik) are working towards extending business intelligence to organizations worldwide. When we talk about business intelligence, there's also this decision intelligence that you've been pushing. How can companies ensure that AI-driven decisions they are making are ethical, fair, and explainable? Forbes: The first step is to identify what that should look like. How our work should be and what are the standards here that we're trying to meet. I know Qlik is very actively working on keeping updated with international standards, as well as NIST (National Institute of Standards and Technology), which is the US government agency that is telling you, having frameworks around the AI, what they should look like, and what the ethics and principles are. A lot of the internal work is looking after this, trying to align, and then teaching their customers and working with them to achieve that. It's something that they're constantly educating businesses on. Last year we had a whole panel with the AI Council on responsible AI. We talked a lot about what generative AI would represent from a responsible point of view and what the practices and processes were that we needed to put in place. Bijin: In a broader sense, when we talk about regulation and governance at this point, it's pretty fragmented because there's no global standard yet. Every country, even the EU, has a different way of looking at it. Are we any closer to a unified global standard on AI ethics and governance? Forbes: It's a very good question, and we did discuss that today. The answer is probably no, not yet, mostly because we still see governments trying to do things in different ways, so we still see fragmentation. And bodies that can set the standards are still working out how to do that well. At least for this year, we are not likely to see much of that, although we did see the AI Act coming out of Europe. What happens is the AI Act has what's called the Brussels effect, which is like they did with the General Data Protection Regulation that regulates data. They did it in Europe, but it has an effect everywhere across the world. In some ways, you might think that the AI Act could be setting that there is a framework there indirectly. Bijin: Talking about AI regulation versus innovation, in your experience, how best can policy makers support innovation without letting the risk with systems slip through the cracks? Forbes: I think there are good models to always look up to by governments that are doing that really well. When I see what the Singaporean and the UAE governments are doing, it's a sign of good leadership at that intersection of innovation and regulation. It's not an easy thing to do because you have to balance it out. You don't want to overregulate and then impose restrictions on innovation. They're doing things like sandboxes, for example, and ways to engage industry in programmes where you kind of test the technology. The industry is teaching you and learning before you actually impose strict regulations. Japan is also doing a lot of that. Those countries are very much abreast of the potential of AI, and they don't want to risk that. Bijin: When we talk about generative AI model deployment with respect to governance, what kind of challenges have you come across? These models come with a host of issues like bias and factual inaccuracies; sometimes the training data lacks quality. Forbes: The challenges start because of the nature of AI right now. You're generating and creating things, and there's a lot of autonomy with that. You can imagine, for example, they can create a whole new piece of art based on Picasso's drawing, and then you have copyright issues. Or you could ask a question, and it can completely hallucinate. You have biases and other issues as well. What is very much needed to prevent that is awareness and ensuring that people that interact with technology have the necessary training and understanding of these limitations. When generative AI first came out, I worked on a project which supported ASEAN countries, all the Southeast Asian countries, on how they would adapt their policies and regulations to generative AI, because what they had before on their traditional AI wouldn't be as appropriate anymore. Bijin: Talking about safeguards, the terminology of 'human in the loop' has been romanticised by Big Tech. Do you think human oversight as of today is sufficient, or is there any need for a more rigorous mechanism in place? Forbes: I think that we need a better level of training and people awareness in working with the tools. I don't think that the majority of people know exactly how the systems work, and so it does become risky if those systems are applied in what the AI Act classifies as high-risk situations. We're gradually getting into a more mature level of being able to monitor and check when things do go wrong. But yes, at the same time the AI gets smarter, we need to get smarter working with AI. Bijin: Coming back to the AI Council, what role do corporate-led AI councils like yours play in shaping real-world governance practices in a broader sense? Forbes: I think it's a very crucial role now that companies operating in this space must bring external expertise to guide their work. I hear a lot from investors in the financial sector that they want to see some sort of assurance that you have processes or you have people in place guiding you along the process. Investors want to see from companies: who do you have on the board and on the leadership team? Do you have the right people guiding your company practices or processes? That is a role that the AI Council has here, and it's shaping up to be the right practice across the world. You pick up a lot on that from the AI Act now, with recommendations that are coming out of governments, which is essential that you have the right people in the right positions. Q: Now we are seeing that job roles are being transformed. What kind of cross-disciplinary training should be prioritised at this point in time to balance this fast-paced job transformation? A: I think there's two sides to this. AI will augment us, and it will bring extreme levels of efficiency for the people that know how to work with AI well. For a lot of people that don't have the necessary access or skills, it will become very difficult, and we might see some inequality there. The question becomes, how do we make sure that everyone is having that training and preparation to use and work with AI? We think about that in a global context, in countries or remote regions where people don't yet have full access to the internet. How can we bring in AI and expect that it's not going to disrupt the workforce when the reality is that the world is already not on an equal path? At the same time that we bring in the technology, we need to be upskilling people. The countries that are doing that very well are countries that have partnerships with governments. They are skilling people. There's a lot of education awareness that we see happening in leading economies. Bijin: If you had to predict, what's the next big ethical question the AI industry will face in maybe 2026? Forbes: Big question. I wouldn't attempt to answer that question. I think that we're going to see exponential growth now. It's just going to accelerate. It is very hard to project in exactly the right direction. There have been statements from AI experts about AGI that we are not far from that within a few years. Some other experts disagree. We have to observe and see. I think that anyone that speaks to that with certainty is probably lying. The author is attending Qlik Connect 2025 in Orlando, US, at the company's invitation. Bijin Jose, an Assistant Editor at Indian Express Online in New Delhi, is a technology journalist with a portfolio spanning various prestigious publications. Starting as a citizen journalist with The Times of India in 2013, he transitioned through roles at India Today Digital and The Economic Times, before finding his niche at The Indian Express. With a BA in English from Maharaja Sayajirao University, Vadodara, and an MA in English Literature, Bijin's expertise extends from crime reporting to cultural features. With a keen interest in closely covering developments in artificial intelligence, Bijin provides nuanced perspectives on its implications for society and beyond. ... Read More
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Business Standard
15-05-2025
- Business
- Business Standard
Qlik unveils agentic experience to simplify data workflows, aid decisions
Qlik, a leading player in data integration, data quality, analytics, and artificial intelligence, on Wednesday introduced its new agentic experience to drive faster decisions and boost productivity by bringing new simplicity to complex data-driven workflows. Besides, the company launched Open Lakehouse, a fully managed Apache Iceberg solution built into Qlik Talend Cloud. These two products were unveiled at Qlik Connect 2025 here for its customers. The agentic experience will provide a single, conversational interface allowing users across the enterprise to interact naturally with data, using specialised AI agents to quickly uncover insights, drive faster decisions, and boost productivity, bringing new simplicity to complex data-driven workflows. At the heart of this continuous innovation is the Qlik engine, a unique technology that indexes relationships across data, enabling the discovery of unexpected connections. This new agentic experience is about removing the distance between data, decisions, and outcomes, Qlik CEO Mike Capone said here. "People want a seamless, conversational way to engage with their data, one that fits naturally into their work and delivers clear, trusted answers in context. We've built this experience to reflect how decisions actually get made in a business," he said. As enterprises face unpredictable market conditions and increasing pressure to make critical decisions rapidly, investments in AI have grown, he said, adding that, with its agentic experience, Qlik is focused on helping customers turn data into timely, high-quality decisions and results. Qlik's agentic experience to be rolled out this summer is specifically designed to empower teams to accelerate both decisions and productivity in rapidly changing environments, he added. Designed for enterprises under pressure to scale faster and spend less, Capone said, Qlik Open Lakehouse delivers real-time ingestion, automated optimisation, and multi-engine interoperability, without vendor lock-in or operational overhead. As organisations accelerate AI adoption, he said, the cost and rigidity of traditional data warehouses have become unsustainable. Qlik Open Lakehouse offers a new path -- a fully managed lakehouse architecture powered by Apache Iceberg that delivers 2.5 times, 5 times faster query performance and up to 50 per cent lower infrastructure costs, while maintaining full compatibility with the most widely used analytics and machine learning engines, he said. "With Qlik Open Lakehouse, enterprises gain real-time scale, full control over their data, and the freedom to choose the tools that work best for them. We built this to meet the demands of AI and analytics at enterprise scale, without compromise," he said. Qlik Open Lakehouse is built from the ground up to meet the scale, flexibility, and performance demands of modern enterprises, without the tradeoffs, he added. During the Qlik Connect 2025, it was also highlighted that despite record AI investment, most enterprises remain stuck in the lab. According to recent IDC research, while 80 per cent plan to deploy agentic AI workflows, only 12 per cent feel ready to support autonomous decision-making at scale. Trust in outputs is eroding amid growing concerns around hallucinations, bias, and regulatory scrutiny, the report said. And as models become commoditised, competitive advantage is shifting, not to those with the most advanced models, but to those who can operationalise AI with speed, integrity, and confidence, it added. The Qlik AI Council emphasised that trust must be designed in, not added later. Execution is the new differentiator, and it only works when the data, infrastructure, and outputs are verifiable, explainable, and actionable. In today's environment, the companies that pull ahead won't be the ones that test the most, they'll be the ones that deliver, the Council said. Observing that the market is short on execution, Capone said, companies aren't losing ground because they lack access to powerful models. "They're losing because they haven't embedded trusted AI into the fabric of their operations. That's why at Qlik, we've built a platform focused on decisive, scalable action. If your data isn't trusted, your AI isn't either. And if your AI can't be trusted, it won't be used," he added. (Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)
Indian Express
14-05-2025
- Business
- Indian Express
‘AI strategy without execution is pointless': CEO Mike Capone at Qlik Connect 2025
'Tons and tons of money is being poured into AI, but we're not seeing the results. Strategy is great, spending money is great, but without execution, it's completely pointless,' said Mike Capone, CEO of Qlik, during his keynote speech at the Qlik Connect 2025. The annual summit held by the software company has industry leaders gathered to throw light on the current state of AI implementation across enterprises, underscoring a concerning reality that amid massive investments most organisations are grappling to move from strategy to execution. In his keynote address, Capone spoke about the state of AI deployment. 'While 86 per cent added AI strategy, only 26 per cent actually deployed at scale. It's a massive gap. It's tragic,' Capone noted. This gap in implementation is seen as a critical challenge for companies that are rushing to embrace the AI wave, especially the recent phenomenon of Agentic AI that focuses on autonomous, goal-directed systems built to take independent actions. '80% of companies are saying they're investing in agentic AI,' Capone explained. 'But again, here's another gap. Only 12% of companies say or feel that their data is actually ready for agentic AI. So here we go again. Let's everybody jump in the water on agentic, but forget that you got to do the work.' Moments into the keynote, Capone welcomed Ritu Jyoti, group vice president and general manager of AI at IDC. On being asked what are the reasons that are impeding AI adoption, 'the first factor is that they (companies) have fragmented data. They have disjointed data and disparate systems leading to ineffective use for AI.' The IDC executive added that the other barriers include AI strategies operating in isolation from corporate strategy, a lack of AI-ready workforce, and overall a cultural resistance due to job security concerns. Jyoti emphasised the transformative potential of agentic AI while separating it from generative AI: 'Gen AI was all about augmenting a human and improving productivity and operational efficiency… If you think about agentic AI, the focus is on agility, adaptability, and timing,' she explained. Jyoti later illustrated her POV with an example. 'If you have a fully autonomous software engineer, you simply provide a high-level goal, like 'build an app to manage company-wide logistics and inventory', and the system delivers it. With generative AI, progress happened at a human scale, improving individual productivity. But with agentic AI, it's humans plus digital labour, allowing work at a speed, scale, and precision no human-only team can match.' Tom Mazzaferro, chief data AI and Analytics officer at Truist also made a brief appearance at the keynote. Masafaro shared insights on how the US bank is navigating the current challenges. 'Every big bank still operates in a hybrid ecosystem, both on ground, in the cloud. For us, it's all about how you bring it together to deliver our business strategy and service our customers and our clients as we go forward,' he explained. Mazzaferro stressed on the importance of partnerships in successful AI implementation. 'For us, we can't do it alone. We need to rely on partners, on key SMEs, on key solutions to deliver success for both our clients, but also for our teammates, for our employees.' When asked what advice he would give to others embarking on similar journeys, Mazzaferro recommended,'figure out what you're going to start. What do you want to achieve? How are you helping your business achieve their goals, their success, their outcomes? How is the technology that you're building and enabling helping your clients be successful?' Regardless of the challenges, organisations are thriving. 'The early adopters, they are kind of being mindful of the risks. They are being careful about their autonomy… but they're jumping ahead and failing fast, learning their lessons, setting up their structure,' Jyoti explained. She cited Johnson & Johnson as an example, which according to The Wall Street Journal is 'using AI for chemical synthesis during drug discovery, to accelerate drug discovery. Capone highlighted that the sole way to succeed was by focussing on the foundation that is trusted data, rather than pursuing specific AI models. 'It is not about models at all. It's about harnessing your data. It's about trusting your data, and it is about embedding AI where it drives outcomes that are tangible, measurable, real.' Both Capone and Jyoti addressed concerns about AI replacing jobs. When asked if everyone will lose their jobs to AI, Capone responded, 'I don't think so. I think people will lose their jobs because somebody got better at AI than you, not because AI took your job.' On the other hand, Jyoti shared a personal anecdote added.'I always joke with my son when I did my engineering, I didn't get a chance to use a calculator. But when he did his engineering, he used a calculator. That doesn't make him less intelligent than me.' Capone wrapped up his keynote with a call to action focused on execution. 'The race isn't coming. It's already on. The winners are not leaning. They're executing now… You've never been more important to your organisations than you are today. So the question is, are you moving fast enough not just to keep up, but to win?' The author is attending Qlik Connect 2025 in Orlando, US, at the company's invitation. Bijin Jose, an Assistant Editor at Indian Express Online in New Delhi, is a technology journalist with a portfolio spanning various prestigious publications. Starting as a citizen journalist with The Times of India in 2013, he transitioned through roles at India Today Digital and The Economic Times, before finding his niche at The Indian Express. With a BA in English from Maharaja Sayajirao University, Vadodara, and an MA in English Literature, Bijin's expertise extends from crime reporting to cultural features. With a keen interest in closely covering developments in artificial intelligence, Bijin provides nuanced perspectives on its implications for society and beyond. ... Read More
Yahoo
02-04-2025
- Business
- Yahoo
Qlik and Q36.5 Pro Cycling Team Continue Partnership to Drive Data-Driven Performance
Qlik powers team strategy as Q36.5 Pro Cycling Team aims for top 5 global ranking PHILADELPHIA, April 02, 2025--(BUSINESS WIRE)--Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence, today announced the renewal of its partnership with the Q36.5 Pro Cycling Team for the third year. The collaboration cements Qlik's role as the team's "26th rider," providing advanced analytics that support pre-race planning, real-time race decisions, and post-race performance analysis. With Qlik, Q36.5 Pro Cycling Team has transformed how it leverages data. Previously reliant on multiple devices and fragmented information, the team now operates with a single source of truth with a new app developed in collaboration with Qlik partner, Differentia Consulting, streamlining decision-making and sharpening its competitive edge. Through real-time insights, Q36.5 Pro Cycling Team is able to refine its race strategy, optimize performance based on race conditions and help to identify top talent. "Qlik's technology has been a game-changer for us," said Doug Ryder, Team Principal of Q36.5 Pro Cycling Team. "Our vision is to rise up the world rankings and win big races, and data is an integral part of that journey. Having access to real-time insight allows us to adapt our strategy dynamically, ensuring our riders are in the best position to succeed. As we continue our journey towards the top, our partnership with Qlik will be instrumental in making data work for us." "The continued partnership between Qlik and Q36.5 Pro Cycling Team exemplifies the transformative power of data," said Chris Powell, Chief Marketing Officer at Qlik. "We've worked closely with the team, listening to their needs and delivering insights that make a real difference on race day. This collaboration is about more than just data, it's about helping Q36.5 Pro Cycling Team think differently – making the right decisions at the right moments to achieve their goals. We're excited to keep pushing the boundaries together." The renewed partnership comes ahead of Q36.5 Pro Cycling Team taking on the many prestigious Spring classics races in April, including the Ronde van Vlaanderen on April 6 and the queen of the one-day classics, the Paris-Roubaix on April 13 and the Giro d'Italia starting on May 9. These events will serve as key opportunities for the team to put Qlik's data-powered insights into action and showcase their evolving strategy. A major step forward in this journey is the addition of Tom Pidcock as the team's lead rider. A powerhouse in professional cycling and Team GB gold medallist, Pidcock's arrival signals a new era of performance and potential for the team. Q36.5 Pro Cycling Team will also be at Qlik Connect 2025, Qlik's flagship global customer and partner event, taking place from May 13-15 in Orlando, Florida. Attendees will have the opportunity to see how Qlik is working with the team to transform its sporting performance and how data-driven decision-making is shaping the future of elite competition. Attendees will also have the chance to raise funds for Special Olympics, donated by Participants will have a chance to compete against their peers, track real-time race metrics, and see their performance come to life on a dynamic Q36.5 Pro Cycling Team dashboard—all powered Qlik. To secure your spot at Qlik Connect 2025, visit About Q36.5 Pro Cycling Team Q36.5 Pro Cycling Team is a professional cycling team committed to innovation, performance, and sustainability. With a focus on integrating advanced technology and data analytics, the team aims to redefine competitive cycling and achieve top global rankings. For more, visit: About Qlik Qlik converts complex data landscapes into actionable insights, driving strategic business outcomes. Serving over 40,000 global customers, our portfolio provides advanced, enterprise-grade AI/ML, data integration, and analytics. Our AI/ML tools, both practical and scalable, lead to better decisions, faster. We excel in data integration and governance, offering comprehensive solutions that work with diverse data sources. Intuitive analytics from Qlik uncover hidden patterns, empowering teams to address complex challenges and seize new opportunities. As strategic partners, our platform-agnostic technology and expertise make our customers more competitive. View source version on Contacts Media Contact Craig +44(0)7795 662 888 Sign in to access your portfolio
