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Attention AI enthusiasts! Are you struggling with processing structured and unstructured data across platforms? You're not alone! According to our recent survey, 100% of attendees face the same challenge. But don't worry, we've got you covered! HPE Ezmeral Software provides seamless access to any data type across on-premises, private and public clouds, and remote locations. Plus, we offer an open analytics layer that enables self-service access to the most popular open-source tools, all wrapped in security and governance. In fact, 60% of our survey respondents said that open source tools with built-in security and governance would empower their AI teams, while 30% said they need a scalable solution to keep pushing the boundaries of AI. HPE Ezmeral Software delivers both! The best part? HPE manages this ecosystem, which means you have access to the freshest versions of these tools without all the heavy lifting. As your expertise with AI grows, so does the platform. Ready to take your AI projects to the next level? Check out this 2-minute solution overview to learn more about HPE Ezmeral Software. #hpeezmeral #hpe #opensource #AI #machinelearning #data #analytics hpe.com/software/brief 

In today's data-driven world, machine learning has become an essential tool. With advances in technology and the increasing availability of data, machine learning has gained popularity in various fields, including healthcare, finance, and manufacturing. Valentino

⏳ Only 2 days left! Secure your seat now. This is the last chance to register to: "How to Maximize Your Edge Data: Transitioning from Connected to an Intelligent Edge", 📅 Date: June 19 🕒 Time: 2 PM CEST 🔗 Register now: https://hubs.la/Q02B_9vm0 🌟 WHY THIS WEBINAR? By 2025, 75% of enterprise-managed data will be processed "at the edge." As the #edge becomes more connected and new use cases emerge, enterprises must consider the right edge #infrastructure to fully leverage their data. 🌟 WHY ATTEND? We will explore the "digital edge journey" of leading industrial organizations, focusing on their challenges and technology requirements as they transition from #datacollection to #onsite #analytics and #machinelearning inferencing at the edge. If you are an: 👷♂️ #OT Digital Leader: You will equip yourself with tools to efficiently manage and maintain distributed assets. 💻 #Infrastructure Manager: You will learn to manage and maintain the lifecycle of #EdgeApplications and #AI models in distributed environments. 🧠 #AI and #Data Lead: You will gain insights into #ModelDeployments and #Training on the field. 🔍 #DigitalTransformation Lead: You will discover the key drivers of successful #edgecomputing deployments to maximize your operational data. Whether you're just beginning to collect data or deep into your digital transformation journey aiming to harness AI at the edge, this webinar is for you! 📍Save your seat here: https://hubs.la/Q02B_9vm0 We look forward to seeing you there! 🎉 #DigitalTransformation, #Digitalization, #IndustrialAI, #IndustrialTransformation, #DigitalTwin, #edgetechnologies #industry40 #smartmanufacturing #technologytrends #edgeAI David Puron Rudy De Anda Dayna Klein Jay David Laura Santagati

👋Join us on June 19 for a #livewebinar "How to maximize your Edge Data: Transitioning from Connected Edge to an Intelligent Edge" organized by Stratus Technologies and Barbara. 💡Why this webinar? Despite the abundance of industry data collected, less than 25% is processed. The main bottleneck? Many enterprises lack the necessary #edge #infrastructure to harness their data effectively. ✨ 🔍Why Attend? We'll explore the challenges faced by leading organizations in their digital journey, from data collection to on-site analytics and real-time inferencing. 👉 Register now and take the first step towards unlocking the full potential of your #edgedata and: 🛠️ Learn from real-world examples of successful Edge Computing deployments. 🔐 Understand the requirements needed for a robust edge infrastructure. ⚡ Achieve real-time #machine learning inferencing 📅 Date: June 19 🕒 Time: 2 PM - 3 PM CEST 📍 Live Webinar 🔗 https://hubs.la/Q02xKYJc0 👉 Register now and take the first step towards unlocking the full potential of your data at the #Edge!✨ Dayna Klein Rudy De Anda David Puron Jay David laura santagati #EdgeAI #DigitalTransformation #DataProcessing #EnterpriseTech #Webinar #Innovation #Edgetechnologies #AI

The importance of data in future manufacturing processes cannot be overstated. It has been seen for years in traditional software industries where every company collects data for various purposes such as targeted advertising. This pattern is expected to extend into manufacturing. The rise of large-scale machine learning algorithms that can predict failures in a production line requires extensive data, necessitating data collection and analysis to be prioritized. Before adopting AI and machine learning, it's crucial to collect and understand the data from the production line. In the short term, this will likely involve implementing more data applications and Manufacturing Execution Systems (MES) to gather the necessary production data. Over the next five to ten years, a surge in AI usage in manufacturing is anticipated. However, the challenge lies in integrating these new data-driven technologies into legacy systems that have been operational for decades. There are a few approaches, including developing a parallel system and then transitioning, which may result in a loss of historical data, or migrating old data from various databases, which can be complex due to discrepancies and the necessity for deep institutional knowledge. Regardless of the chosen approach, a significant push towards data integration is predicted, leading to greater automation and efficiency in manufacturing processes. Decision-making is also expected to become increasingly data-driven, with MES applications helping to track products throughout the manufacturing process. Even C-suite executives are beginning to have these applications readily available on their desktops. Ultimately, the data-centric approach is what seems to define the future of manufacturing, at least for the next five years. This will likely result in fewer people needed on specific production lines and more automated processes, impacting business models and operational procedures in the industry. This clip was taken from Manufacturing Hub Episode 119 - https://lnkd.in/egY9-x7J With guest - Addison Waege #manufacturing #automation #data #industry40 #digitaltransformation

The importance of data in future manufacturing processes cannot be overstated. It has been seen for years in traditional software industries where every company collects data for various purposes such as targeted advertising. This pattern is expected to extend into manufacturing. The rise of large-scale machine learning algorithms that can predict failures in a production line requires extensive data, necessitating data collection and analysis to be prioritized. Before adopting AI and machine learning, it's crucial to collect and understand the data from the production line. In the short term, this will likely involve implementing more data applications and Manufacturing Execution Systems (MES) to gather the necessary production data. Over the next five to ten years, a surge in AI usage in manufacturing is anticipated. However, the challenge lies in integrating these new data-driven technologies into legacy systems that have been operational for decades. There are a few approaches, including developing a parallel system and then transitioning, which may result in a loss of historical data, or migrating old data from various databases, which can be complex due to discrepancies and the necessity for deep institutional knowledge. Regardless of the chosen approach, a significant push towards data integration is predicted, leading to greater automation and efficiency in manufacturing processes. Decision-making is also expected to become increasingly data-driven, with MES applications helping to track products throughout the manufacturing process. Even C-suite executives are beginning to have these applications readily available on their desktops. Ultimately, the data-centric approach is what seems to define the future of manufacturing, at least for the next five years. This will likely result in fewer people needed on specific production lines and more automated processes, impacting business models and operational procedures in the industry. This clip was taken from Manufacturing Hub Episode 119 - https://lnkd.in/egY9-x7J With guest - Addison Waege #manufacturing #automation #data #industry40 #digitaltransformation

The importance of data in future manufacturing processes cannot be overstated. It has been seen for years in traditional software industries where every company collects data for various purposes such as targeted advertising. This pattern is expected to extend into manufacturing. The rise of large-scale machine learning algorithms that can predict failures in a production line requires extensive data, necessitating data collection and analysis to be prioritized. Before adopting AI and machine learning, it's crucial to collect and understand the data from the production line. In the short term, this will likely involve implementing more data applications and Manufacturing Execution Systems (MES) to gather the necessary production data. Over the next five to ten years, a surge in AI usage in manufacturing is anticipated. However, the challenge lies in integrating these new data-driven technologies into legacy systems that have been operational for decades. There are a few approaches, including developing a parallel system and then transitioning, which may result in a loss of historical data, or migrating old data from various databases, which can be complex due to discrepancies and the necessity for deep institutional knowledge. Regardless of the chosen approach, a significant push towards data integration is predicted, leading to greater automation and efficiency in manufacturing processes. Decision-making is also expected to become increasingly data-driven, with MES applications helping to track products throughout the manufacturing process. Even C-suite executives are beginning to have these applications readily available on their desktops. Ultimately, the data-centric approach is what seems to define the future of manufacturing, at least for the next five years. This will likely result in fewer people needed on specific production lines and more automated processes, impacting business models and operational procedures in the industry. This clip was taken from Manufacturing Hub Episode 119 - https://lnkd.in/egY9-x7J With guest - Addison Waege #manufacturing #automation #data #industry40 #digitaltransformation

Although generative AI may be the latest focus of the C-suite agenda, your CIO mandate for 2024 is a familiar one: direct the way the business leverages this and other emerging technologies to increase productivity and revenue. Learn more from PwC about what's important to CIOs in 2024: https://lnkd.in/dw4PEiGf Again another interesting read!😀👍📖

1.   #DigitalTwin and #BigData in #Manufacturing 2.   Characteristics of The #DataDriven Enterprise: Application and Key Enablers 3.   Modern #Data Solutions: Fueling the #AI Revolution (12 Industry Use Cases) 4.   #EnterpriseArchitecture: Connecting #Maturity and Value (4 Case studies) 5.   Successful Enterprise Strategies in Adopting #Industry40 (Case Studies) 6.   US Department of Defense - #Digital #Modernization Strategy These are the Six Headlines of Our Yesterday’s Premium Content. Details are available to our email subscribers. (To subscribe to our Premium Content, you can DM me or email to info@transformpartner.com for the details) Image Source: Digital Twin #SolutionArchitecture, Software AG #TransformPartner – Your #DigitalTransformation Consultancy

In today's manufacturing world, tapping into data's full potential is crucial for innovation and efficiency. But manufacturers face hurdles like boosting equipment effectiveness, scaling digital solutions, maintaining legacy systems, addressing labor shortages, and managing rising costs. 🌟 How to revolutionize #manufacturing by unifying IT and OT data? This synergy empowers manufacturers with actionable insights, supercharging production efficiency. With Microsoft Fabric manufacturers can get actionable insights and boosts production efficiency using natural language with #genAI #Copilot 🏭💡 📊 The future of manufacturing is data-driven. With Fabric’s advanced AI readiness and alignment with ISA-95 standards, we’re not just optimizing operations; we’re redefining them. Let’s innovate for a smarter, more connected manufacturing world! ⁉️ How do you use tech to get insights from your data? Comment below! ⤵️ Dominik Wee, Simon Floyd, Katy Brown, Tony Harris, Amanda Anderson, MBA, Jason Rowe, Dane Wentworth, John Reed, Dan Aldridge, ERP Software Expert, Tracy Galloway, Jeff Winter, Pascal BORNET Learn more https://lnkd.in/gRvGaMw7 Introducing new manufacturing data solutions in #MicrosoftFabric and copilot template for factory operations on Microsoft #AzureAI. https://lnkd.in/gSZ86JV7 #cloudformanufacturing #innovation #MicrosoftFabric #DataDrivenManufacturing