Software AG’s Post

Operators are telling us that the massive hype around #generativeAI, which has caught the attention of company boards across the industry, is shining a spotlight on their need for data transformation. Without high quality, consistent and common internal data sets, operators will struggle to apply generative #AI.  Many operators still have highly siloed data architectures across their business units. Although some have made great progress in de-siloing customer data, operators are generally at very early stages of transforming their network data infrastructure, arguably a much more difficult challenge. However, continuing with network data silos will make the application of generative AI to this domain difficult and also prevent operators from effectively deploying the analytics-driven operational architectures needed to drive autonomous networking, a key operational goal. My colleague, Adaora Okeleke, has just published a new report, Modernising CSPs’ data architectures for network analytics/AI-driven automation, which lays out these challenges and looks at how operators are resolving them. The report draws on the experiences of three leading operators that are positioning themselves well to exploit real-time network analytics at scale through the transformation of their network data architectures. This positioning will also enable the operators to capitalise on generative AI when the technology matures enough to be applied, alongside other AI approaches, to network automation. The report is a recommended read for anyone wanting to understand best practices for network data transformation today - https://lnkd.in/eNPpVWBE

AITech365’s Weekly Roundup: Discover the Most Recent News From IBM, Seeq Corporation, Riverbed Technology, H2O.ai! https://lnkd.in/dbzsvJVj #AI #analytics #Automation #GenerativeAI #news #RoundUp

Successful platforms unite the right data, model architectures, governance, and computing infrastructure to enable reliable value creation across the ecosystem, with “anyone, anywhere.”

Save the date! November is undoubtably the best month (no bias for birthdays) and it just got sweeter. Register below and join the awesome Oliver Perilli & Andrew Gadsby for their live webinar where they will discuss: • how other industry pros have approached their modernization projects & addressed critical issues with data analytics solutions • understand how to preserve your investment in business-critical applications by bringing modern analytics technologies into a coherent, future-proof platform • learn how to address the challenges that come with modernization - from staff skills & budget restraints to organizational friction See you there! #altair #onlyforward #webinar #dataanalytics #ai #project #customersupport

Retrofit or rebuild the workload? 🤖 #theCUBE explores #enterpriseAI trends In this #SASInnovate 2024 keynote analysis, #theCUBE research analysts dig into the retrofitting vs. rebuilding workload models, discussing AI’s capabilities and SAS’ legacy installation. “There's this idea that you don't need to raise the house and bulldoze everything. You can retrofit your workload if you've got an end-to-end workload, like procurement workload. To bring AI to it, you redesign or retrofit vs. rebuild the whole thing. Do you guys see it that way?” John Furrier asks the panel. “For these guys, the challenge that SAS has is they got a lot of old legacy stuff that is big. It's a big part of their install base and the new stuff is growing at 30%. It's a good growth rate, but not big enough to offset the 10% decline,” says David Vellante, acknowledging SAS’ monetization success and obstacles. The panel goes on to discuss industry business models that have explored the rewriting of the whole stack. Efforts to reimagine the entire supply chain can be an appropriate decision, but legacy systems require a balanced management approach. 📺 Get into the full discussion: https://lnkd.in/eT8txfgi

Check out this MuleSoft blog and learn how distributed tracing enables modern IT observability by offering a view of application performance which is more detailed than what can be gleaned from traditional logs and metrics.

The Importance of Verifiable Storage in AI and Machine Learning ℹ️In the rapidly evolving fields of AI and machine learning, the integrity and security of data are paramount. Verifiable storage ensures that data used in training and inference is accurate and has not been tampered with, leading to more reliable and trustworthy AI models. Additionally, it enhances transparency and accountability, which are critical for regulatory compliance and building user trust. ✅ARData.Tech offers solutions that ensure data is tamper-proof and tamper-evident, providing robust verifiable storage mechanisms essential for leveraging AI and machine learning technologies. For more information and to discuss your needs, book a call with us today at https://ardata.tech.

The AI readiness projects that many of you are undertaking can be overwhelming. If you're in #operations or #engineering for mission critical systems, this might be a good read. Phaidra is changing the nature of industrial controls and bringing far more powerful software into the sphere that has been dominated by tools and protocols developed 40 years ago. The future looks very different than the current state as the world shifts to fundamentally better software architectures. These new techniques demand better and more rich data sets in order to give best results. Start with better data. https://lnkd.in/gqaADhBK

Here is my latest blog about: Mastering OpenTelemetry: Proven Techniques for Achieving Seamless Traceability - https://lnkd.in/gcsMQm4q Title: Mastering OpenTelemetry: Unleashing Traceability for Unparalleled Insights Introduction: In today's digitized world, organizations around the globe are collecting vast amounts of data, striving to uncover the hidden metrics that shape their success. Among the myriad tools available, OpenTelemetry emerges as a groundbreaking solution, enabling seamless traceability by capturing and analyzin... Do Like & Share :)

In the landscape of FY2024E, the financial sector stood at the forefront of innovation. Customer Interaction Services & Finance & Accounting emerged as the cornerstones of the domestic BPM market, commanding 55-65% share. This dominance underscored the sector’s proactive approach to meeting evolving consumer demands. Notably, database development for AI adoption emerged as a pivotal growth driver, signaling a strategic shift towards technology integration. #finance #AI #BPM