Podcasts about rapidminer

Listen to my interview with Ingo Mierswa, founder of RapidMiner and SVP of Product Development at Altair, as we explore the integration of RapidMiner technology into the Altair RapidMiner Platform and the recent acquisition of Cambridge Semantics' knowledge graph technology. Discover how Altair is delivering an end-to-end data science solution and why it was named a Leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms.

Steve Rader is a leader in the thinking behind open innovation, open talent, and the future of work. In this episode of The Evolving Leader podcast, Steve joins Evolving Leader cohosts Jean Gomes and Scott Allender to share how leaders can learn from his important work and use their learnings to solve complex problems. Steve tells us that open innovation and open talent are key strategies for organisations to stay competitive in a rapidly changing world.References from this episode:"Co-Intelligence: Living and Working with AI" by Ethan Mollick (April 2024)RapidMiner (https://altair.com/altair-rapidminer)Other reading from Jean Gomes and Scott Allender:Leading In A Non-Linear World (J Gomes, 2023)The Enneagram of Emotional Intelligence (S Allender, 2023)Social:Instagram           @evolvingleaderLinkedIn             The Evolving Leader PodcastTwitter               @Evolving_LeaderYouTube           @evolvingleader The Evolving Leader is researched, written and presented by Jean Gomes and Scott Allender with production by Phil Kerby. It is an Outside production.Send a message to The Evolving Leader team

I'm trying something new this week: These show notes were generated by putting a transcript into ChatGPT. Feedback is appreciated! —Randy We recently heard Jeff Marraccini on the "This Week in Enterprise Technology (TWiET)" podcast. Jeff, the Chief Information Security Officer (CISO) at Altair, joined us this week to share insights into his background and the challenges Altair faces in cybersecurity as a globally acquisitive company. The conversation explores Jeff's transition from a Vice President of IT to a CISO, underscoring the importance of continuous learning and formal courses from ISC2 and ISACA to adapt to the evolving cybersecurity landscape. Emphasis is placed on the complex vendor landscape in cybersecurity and the need to implement zero trust as a methodology rather than just a product. Jeff delves into Altair's approach to global operations, collaborating with teams across China, India, Europe, and the United States. Regulatory challenges, such as restrictions on hardware in China, are discussed. The podcast concludes with a discussion on the evolving cybersecurity landscape, highlighting Jeff's optimism about advancements like memory-safe languages and Microsoft's adoption of Rust. Despite existing challenges, Jeff sees promising developments and disruptive solutions in the cybersecurity space. A noteworthy segment of the discussion involves the importance of identity in cybersecurity. Jeff and Bob emphasize that identity management should be at the crux of security efforts, recognizing its role as a foundational element for effective cybersecurity measures. The conversation highlights the shift in focus from traditional security measures, like firewalls, to a more comprehensive approach centered around identity management. Furthermore, Bob and Jeff touch upon the evolution of cybersecurity news coverage. They discuss the noticeable decrease in mainstream media coverage of security breaches, speculating on whether this shift is influenced by the insurance industry advising companies to keep incidents quiet or if it reflects a change in news priorities. Jeff acknowledges the continued prevalence of security issues covered by specialized outlets like the Cyberwire podcast, CSO Online, and Dark Reading. Towards the end, the conversation pivots to the impact of Gen AI (Generative Artificial Intelligence) and digital transformation on the industry. Jeff shares insights into Altair's recent acquisition of RapidMiner, emphasizing the empowerment of individuals to leverage AI techniques for various applications, including data science and cybersecurity. The discussion underscores the potential for Gen AI to enhance efficiency and collaboration across different fields. The podcast concludes with Bob raising a concern about the younger generation's reluctance to pursue careers in IT, especially in areas like cybersecurity and data science. Jeff offers guidance, encouraging individuals to explore these fields through online courses and hands-on projects, emphasizing their applicability across diverse industries. The conversation touches on the need for a shift in mindset and the potential for technology-driven roles to drive innovation and problem-solving. Overall, the discussion provides a comprehensive overview of cybersecurity challenges, industry trends, and the transformative impact of emerging technologies.

Using Ai to Brand Your Name and Business, Part 26/12/23How can AI be leveraged to better understand your past business successes and failures?Use Ai to find out the top reasons why businesses fail and ask for a plan to combat the predicted failures for your businessAsk Ai to give top reasons why businesses succeed and a plan to succeed for your businessUse Ai to put in data of your successes in business and ask it to analyze itUse Ai to put in data of your failures in business and ask it to analyze it and what you can do so the failures won't happen againUse Ai to discover trends and draw your audience inUse Ai to identify successful strategies as well as improve your decision-makingUse Ai to find out what your voice is for your businessUse Ai to discover the financial trends for your business and ask for a strategies to useUse Ai for personalizing experiences Use Ai to analyze customer feedbackUse Ai to analyze your salesUse Ai to keep track of the people visiting your websiteUse Ai to automate your tasksUse Ai to analyze the money coming in and going out, then asking how to improve more money coming in Use Ai to keep your audience engaged on social mediaHow could AI have enhanced the growth of the family liquor store if it had been implemented earlier?How might AI reveal hidden trends or patterns in your past marketing data that you may have missed?How can AI automation transform the scale and speed of your business processes?How could using AI to analyze your business data lead to the development of innovative marketing strategies?Can AI assist in personalizing your branding to resonate more effectively with your target demographic?How might AI's predictive analytics improve your future marketing campaigns and customer interactions?In what ways can AI transform your understanding of your customer base?How might AI challenge our conventional understanding of effective branding and marketing?How can AI help in minimizing the risk while planning for business expansion?How can AI assist in identifying market trends before they become mainstream?How could you use AI to monitor and improve your brand reputation online?How might machine learning help refine your sales and marketing strategies over time?How can AI-based customer segmentation transform your business development efforts?How would you gauge the readiness of your business to fully embrace AI?What obstacles might a business face when trying to integrate AI into their existing processes?How might AI simulation modeling provide an edge in strategic planning for your business?How could AI reveal potential opportunities for diversification or expansion?Can AI be instrumental in optimizing resource allocation for business development?How can AI enhance customer engagement and retention for your brand?What ethical considerations should you be aware of when implementing AI in your business?How would you manage the potential challenges of privacy and data security with AI?How might you leverage AI to forecast future trends in your industry?How can AI revolutionize your approach to competitive analysis?How might AI transform the way you measure the success of your marketing campaigns?How can the power of AI be harnessed to create more effective, targeted ad campaigns?What steps could be taken to future-proof your business against rapid advancements in AI technology?How might AI redefine the way you understand and respond to your customers' needs and preferences?What roles within your business could AI potentially take over, and how might this affect your existing team structure?How can AI be used as a tool for continuous learning and evolution in your business?Useful Tools to Analyze the Past Business Successes and Failure to Improve in Your BusinessTensorFlow: It's like a super-smart toolbox that helps computers learn from data. It can analyze lots of information about your business and find patterns to understand what worked and what didn't.IBM Watson: Imagine having a really smart friend who knows a lot about businesses. Watson uses AI to analyze data and provide insights on successes, failures, and trends, helping you make better decisions.Google Analytics: It's like a special detective that looks at data from your website and tells you which parts are working well and which ones need improvement. It helps you understand what your customers like.Amazon Personalize: Imagine a friendly assistant who knows exactly what you want. This software uses AI to understand individual customers and suggests personalized offers or products, making them happier.Microsoft Azure Machine Learning: It's like a brain that helps computers understand and analyze data. It can predict what might happen in the future based on past information, so you can make smarter decisions.Salesforce Einstein: Imagine a smart helper who can understand your customers' preferences. Einstein uses AI to analyze data and recommends the best strategies to improve your business success.Tableau: Think of it as a magical painting that shows you important information about your business. Tableau uses AI to visualize data in colorful charts, making it easier for you to understand patterns and trends.RapidMiner: It's like a powerful detective that finds hidden patterns in your business data. RapidMiner uses AI to analyze information and discover successful strategies, helping you make better decisions.H2O.ai: Imagine having a magic crystal ball that can predict the future of your business. H2O.ai uses AI to analyze data and make predictions, so you can plan ahead and adapt to changing trends.Alteryx: It's like a magic potion that automates repetitive tasks. Alteryx uses AI to handle data analysis and other tasks, freeing up time for you to focus on creative and strategic aspects of your business.Support this podcast at — https://redcircle.com/the-secret-to-success/exclusive-contentAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Every day we make decisions. Some are as simple as deciding when to leave for work in order to beat traffic or what to eat for breakfast. Others bear much greater importance, such as what new products to launch or what new markets to tackle. Analytics plays an important role in helping your business make these decisions in a smarter, more data-driven way.“The purpose of analytics is to help us make decisions, is to create decision-making capabilities across the company. The next step was to find out what those decisions are that we would need to make? When I say decisions, these are not like once in a quarter, boardroom decisions. I'm talking about everyday decisions that many of our colleagues make every single day.”Vijay Kotu is the SVP of Data and Analytics for ServiceNow, a company that is helping enterprises manage digital workflows. In this episode of the Data Chief, Vijay discusses how he is building a high-growth “mathematical enterprise” where frontline workers are empowered to make smarter business decisions with data and AI. He also speaks about the impact of ecosystems, the need for businesses to have a holistic view of their data in order to create positive outcomes, and why being intentional about analytics use cases is absolutely essential. Key Takeaways:Don't underestimate the impact of micro-decisions: We all want to be more data-driven, but don't fall into the trap of thinking that data and analytics can only be applied to once-a-quarter, boardroom-level decisions. Enabling frontline employees to be more data-driven in their everyday work is a hugely powerful way to make a positive impact across your entire business.Evaluate how data can improve workflows: The holy grail of analytics is converting insights to action. One of the most effective ways to do this is by automating workflows whenever and wherever possible. With automation, you help everyone in the business be more efficient without adding any extra work or manual decision-making.Data becomes exponentially more powerful when it's connected: Having all of your proprietary data in one place is a great way to start your data journey but it becomes exponentially more valuable when you connect it to outside data sources. Bringing together multiple sources of data gives you even richer insights about your customers, employees, and products.Data serves the business: At the end of the day, your data goals should align with that of businesses. Data and analytics professionals must remember that data is there to serve sales, marketing, product, IT, etc. into making better decisions for the business. They are the ones running the functions and the data and analytics teams are the backbone of that. Therefore, data teams should be designing products with that in mind.Key Quotes“The purpose of analytics is to help us make decisions, is to create decision-making capabilities across the company. The next step was to find out what those decisions are that we would need to make? When I say decisions, these are not like once in a quarter, boardroom decisions. I'm talking about everyday decisions that many of our colleagues make every single day.”“Data just in one place, it's less valuable. But when you connect it with other data points that you have, it becomes even more valuable.”“What are you going to do with those insights? That would be the actions. If these insights are helping you make a decision, how do we actually put that decision in action is closing the loop. That has been the Holy Grail of analytics. Rather than stopping at insights, you're closing the loop on helping people do that action here.”“The things that matter the most for our customers right now is a prioritization decision, and doing really well in those areas will help us reach further in our goal.”Bio:Vijay Kotu is Senior Vice President of Analytics at ServiceNow. He leads the implementation of large-scale data platforms and services to support the company's enterprise business. He has led analytics organizations for over a decade with focus on data strategy, business intelligence, machine learning, experimentation, engineering, enterprise adoption, and building analytics talent. Prior to joining ServiceNow, he was Vice President of Analytics at Yahoo. He worked at Life Technologies and Adteractive where he led marketing analytics, created algorithms to optimize online purchasing behavior, and developed data platforms to manage marketing campaigns. He is a member of the Association of Computing Machinery and a member of the Advisory Board at RapidMiner.To hear more about ServiceNow, check out their podcast.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company's data for insights doesn't have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com. 

RapidMiner bietet eine der führenden Data Science Plattformen an, kommt ursprünglich aus Dortmund und hat dort immer noch den größten Teil der Forschungsabteilung. In dieser Podcast-Episode unterhalte ich mich mit Ralf Klinkenberg, Mitgründer und Forschungsleiter bei RapidMiner. RapidMiner: https://rapidminer.com/ LinkedIn Ralf Klinkenberg: https://www.linkedin.com/in/klinkenberg/ LinkedIn Dr. Bernard Sonnenschein: https://www.linkedin.com/in/bernardsonnenschein/ Ich freue mich über Feedback: bernard.sonnenschein@datenbusiness.de Unsere Themen: Die Geschichte hinter RapidMiner. (ab 01:11) Wurzeln in Dortmund, HQ in Boston. (ab 07:56) Use Cases. (ab 12:15) Die Stärken von RapidMiner: Flexibilität, Modularität, Einfachheit. (ab 23:33) Brauchen wir mit Plattformen wie RapidMiner weniger Data Scientists? (ab 29:44) Transparenz im Tool und im Pricing. (ab 35:53) Agilität und Innovationsgeschwindigkeit hat im Markt zugenommen. (ab 39:04) Viele Anwender brauchen mehr als AutoML. (ab 42:01) Augmented Analytics. (ab 45:24) Trendthema IIoT (mit Bezug auf Actyx). (ab 52:01)

In this episode, I had a guest on the podcast: Zoltan Prekopcsak (VP of Data Science and Analytics at Prezi, previously VP of Data Science at RapidMiner). I asked Zoltan to share his story focusing on one question: How did he get his first data science job -- or in other words: how did he become a data scientist? It's a pretty interesting and exciting interview, where you can hear about the first steps of a now-senior data professional. Zoltan talks about his side projects, about the data science competition he enrolled in with his friends (back in 2007!), about his first internship and eventually his first junior data scientist position. MENTIONED IN THE EPISODE: Zoltan's Linkedin Profile: https://www.linkedin.com/in/preko/ RapidMiner: https://rapidminer.com/ Prezi: https://prezi.com/ Netflix Competition: https://en.wikipedia.org/wiki/Netflix_Prize Kaggle: https://kaggle.com/ StackOverFlow: https://stackoverflow.com/ Secret Sauce Partners: https://secretsaucepartners.com/ -------- Check my website: https://data36.com Get access to more data science tutorials, join the inner circle: https://data36.com/inner-circle Find me on Twitter: https://twitter.com/data36_com

In the inaugural episode of The Bowdoin Group's podcast series, "Decoding the Journey," our own Jim Urquhart connects with Peter Lee, tech entrepreneur and current CEO of RapidMiner, the Boston-based data science platform that unifies data prep, machine learning, and model operations.

Ebben a BB extrában a data science került fókuszba. Gáspár Csaba és Nagy-Rácz István - a dmlab vezetői - voltak Tomi vendégei. Az interjú legizgalmasabb pontjai (a teljesség igénye nélkül): - Csaba és István egyszerre data scientist-ek és cégvezetők, mesélnek arról, hogy hogyan tudnak ezek között a szerepek között egyensúlyozni - a dmlab már több, mint 10 éve a piacon van, az egyik legnagyobb múltú magyar adatos cég. Így az interjúban hallhatunk az adatos hősidőkről is. (Pl. growth hacking a startlapon ;-) - a dmlab-nak több startup-jellegű spin-off-ja is volt. Ezekből pl. a Radoop exit-tel zárult: a RapidMiner vásárolta fel. Erről a sztoriról is mesélnek vendégeink. - szó esik arról is, hogy mi az igazi különbség az adatbányászat, a data science és az AI (mesterséges intelligencia) között - és még sok-sok-sok minden másról... LINKEK: - http://dmlab.hu/ - https://bizniszboyz.hu/mi-az-a-data-science/ Kövesd a BB-t mindenhol: Zárt csoport: https://www.facebook.com/groups/bizniszboyzpodcast/ Insta: https://www.instagram.com/bizniszboyz/ Cikkek és kontakt: https://bizniszboyz.hu/ Indítsd podcast-et, segítünk benne: https://bizniszboyz.hu/indits-podcast-et-a-cegednek-a-markadnak-segitunk/

Ralf Klinkerberg, one of the founders of RapidMiner, a leading data science platform shares his views on what is artificial intelligence, data mining, deep learning, data science. We discuss the applications in business, the success factors for companies implementing AI and the potential of AI for society and business.

You hear a lot about serial entrepreneurs. But in this Operations episode, Sean sits down with a serial operator. Heidi Rawding is the Senior Director of Operations at RapidMiner and has been hired as the first ops person at three different companies. Meaning she's gone through hypergrowth and has built the foundation for an ops organization three different times. Heidi talks about what it's like to start an ops org from the ground-up, how she's built a community of operators, and why she thinks that every ops pro should have a background in hospitality.

Es haben uns Fragen von Ihnen/Euch erreicht - wir hoffen, wir konnten sie befriedigend beantworten. Wer noch mehr wissen will, gerne per Mail oder LinkedIn.

What has big data got to do with your content strategy? It's about using the information you collect and store to create powerful personalised messages. That's all well and good, but what does it mean to your workflow if you have to write to, call, text and Facebook all your customers personally? How can you make your content production flow efficient without losing the personal touch? We talk to big data marketing expert about the possibilities of big data magic, Graeme Noseworthy of RapidMiner in Boston, a former IBMer working with the Watson Foundations Big Data & Analytics Platform. We also chat to Dr Michael Wu, Chief Scientist at Lithium Technologies who is the number cruncher and data miner behind the social software provider to the likes of Barclays, Virgin Atlantic and Time Warner Cable. He explains where big data is now, where some companies are missing a trick and what the future looks like.

You hear a lot about serial entrepreneurs. But in this Operations episode, Sean sits down with a serial operator. Heidi Rawding is the Senior Director of Operations at RapidMiner and has been hired as the first ops person at three different companies. Meaning she's gone through hypergrowth and has built the foundation for an ops organization three different times. Heidi talks about what it's like to start an ops org from the ground-up, how she's built a community of operators, and why she thinks that every ops pro should have a background in hospitality.