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RapidMiner Names New President and CEO

RapidMiner announced former TIBCO EVP, Peter Y. Lee, to the position of President and CEO.

Lee, who also joins the Board of Directors, will focus on the strategy and operations of the company. Founder and fellow Board Member Ingo Mierswa, formerly CEO, will focus on the platform’s evolution as Chief Technology Officer.

At TIBCO, Lee was responsible for the Analytics/Big Data, B2B, Cloud, CXM and SIEM product groups. Lee joined TIBCO when it acquired DataSynapse, where he served as CEO and co-founder. Lee resigned from TIBCO to co-found Mister Wolf & Associates, returning to his entrepreneurial passion advising growth companies such as Attivio, BlogTalkRadio, Ektron, Infomatix, Novus, NOPSEC, Reonomy, SecurityScoreCard and others in disrupting established markets.

“RapidMiner tripled its product revenue in 2014. We needed a seasoned executive and entrepreneur to further propel the company’s leadership in the predictive analytics market. Peter Lee was the clear choice,” said RapidMiner Founder Ingo Mierswa. “With Peter’s deep domain expertise, RapidMiner will help our customers realize substantial value from their analytics and Big Data investments.”

“Organizations have yet to monetize the massive potential hidden in their strategic data assets—a mother lode of priceless insights is buried in a relentless avalanche of Big Data. Moreover, insight without action delivers zero value,” says Lee. “RapidMiner enables organizations to achieve game-changing competitive advantages by unearthing and including predictive analytics in any business process. Operationalizing predictive analytics to confidently seize opportunity or mitigate risk is a must-have capability to close the loop between insight and action.”

Lee earned an MBA in Entrepreneurial Management from The Wharton School, an MA in International Affairs from The University of Pennsylvania and graduated AB cum laude from Harvard University. He serves as Chairman of the Board of Attivio and as an Independent Member of the Investment Committee of the Advanced Finance & Investment Group. Lee has previously served on the Boards of Ektron (acquired by Accel-KKR, merged with EpiServer) and Upwardly Global. He is actively involved in a number of community interests.

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RapidMiner Names New President and CEO

RapidMiner announced former TIBCO EVP, Peter Y. Lee, to the position of President and CEO.

Lee, who also joins the Board of Directors, will focus on the strategy and operations of the company. Founder and fellow Board Member Ingo Mierswa, formerly CEO, will focus on the platform’s evolution as Chief Technology Officer.

At TIBCO, Lee was responsible for the Analytics/Big Data, B2B, Cloud, CXM and SIEM product groups. Lee joined TIBCO when it acquired DataSynapse, where he served as CEO and co-founder. Lee resigned from TIBCO to co-found Mister Wolf & Associates, returning to his entrepreneurial passion advising growth companies such as Attivio, BlogTalkRadio, Ektron, Infomatix, Novus, NOPSEC, Reonomy, SecurityScoreCard and others in disrupting established markets.

“RapidMiner tripled its product revenue in 2014. We needed a seasoned executive and entrepreneur to further propel the company’s leadership in the predictive analytics market. Peter Lee was the clear choice,” said RapidMiner Founder Ingo Mierswa. “With Peter’s deep domain expertise, RapidMiner will help our customers realize substantial value from their analytics and Big Data investments.”

“Organizations have yet to monetize the massive potential hidden in their strategic data assets—a mother lode of priceless insights is buried in a relentless avalanche of Big Data. Moreover, insight without action delivers zero value,” says Lee. “RapidMiner enables organizations to achieve game-changing competitive advantages by unearthing and including predictive analytics in any business process. Operationalizing predictive analytics to confidently seize opportunity or mitigate risk is a must-have capability to close the loop between insight and action.”

Lee earned an MBA in Entrepreneurial Management from The Wharton School, an MA in International Affairs from The University of Pennsylvania and graduated AB cum laude from Harvard University. He serves as Chairman of the Board of Attivio and as an Independent Member of the Investment Committee of the Advanced Finance & Investment Group. Lee has previously served on the Boards of Ektron (acquired by Accel-KKR, merged with EpiServer) and Upwardly Global. He is actively involved in a number of community interests.

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.