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Thomson Reuters nombra a Uiclecia Lima como directora del Centro de Soluciones y Preventas para América Latina
Con más de 20 años de experiencia en transformación digital y mejora continua en áreas como contabilidad, finanzas, cadena de suministro, logística y gobernanza Lima es una adición estratégica al equipo de Corporates LatAm Continue reading Thomson Reuters nombra a Uiclecia Lima como directora del Centro de Soluciones y Preventas para América Latina
#Centro de Soluciones#Corporates#ERP#Nombramiento#OpenText#Oracle#Preventas#Salesforce#SAP#Thomson Reuters#Uiclecia Lima
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Education Industry - Open Text Corporation Dec 2003 Archived Web Page
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Are you grappling with SAP system inefficiencies that hinder your organization's growth? Are you seeking strategies to enhance customer experience (CX) while optimizing operational processes? Look no further.
Join us for an insightful webinar organized by OpenText and ImpactQA on May 22nd at 11 AM ET/10 AM CT. In this 40-minute session followed by a 20-minute Q&A, we'll delve into cutting-edge approaches to streamline SAP systems and elevate CX.
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Unlocking Sustainability: The Role of Digital Transformation | CeBoz.com
Exploring the intersection of digital transformation and sustainable development.
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Unleash the Power of Human Resource
🚀 Exciting #Webinar Alert! 🚀
Join us for an upcoming webinar that promises to reshape the future of HR management. This event is your opportunity to gain exclusive insights into innovative solutions that will enhance efficiency, collaboration, and security in your organization.
Save the date and stay tuned for more details. Don't miss this chance to transform the way you handle HR. Stay connected for registration information and get ready to unlock the potential of your Human Resources!
#HRManagement#HumanResources#OracleHCM#oraclefusion#oraclefusioncloud#HumanResourceManagement#OpenText#OpenTextECM#ECM#humancapitalmanagement#HR#HumanResource#Dubai#AbuDhabi#UnitedArabEmirates#Riyadh#SaudiArabia#Kuwait#Qatar#Bahrain#Oman#Egypt
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In the complex realm of SharePoint migrations, governance emerges as the linchpin for success. The SharePoint Migration Framework provides the tools, but it is governance that shapes the strategy, ensuring that migrations are not only technically sound but also aligned with organizational goals. As organizations navigate the intricate process of migrating to or within SharePoint, a robust governance plan becomes the guiding light, ensuring a seamless transition, user satisfaction, and long-term success. With tools like Tzunami Deployer in the toolkit, organizations can elevate their migration experience to unprecedented levels of efficiency and reliability, solidifying their position as leaders in the digital transformation journey.
#Atlassian Confluence#Documentum#Livelink#OpenText Content Server#sharepoint migration framework#sharepoint migrations#Xerox DocuShare
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OpenText VIM: Streamlining Vendor Invoice Management in 2023
Are you searching for an efficient solution to manage your enterprise content seamlessly? Look no further than OpenText VIM. In this article, we’ll explore the myriad benefits of OpenText VIM and how it can streamline your content management processes. Read on to discover how this powerful software can transform your business. What is Opentext vim? OpenText Vendor Invoice Management (VIM) is a…
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#opentext vim#opentext vim sap#SAP VIM#vendor invoice management#VIM#vim by opentext#vim opentext#vim opentext sap#what is opentext vim
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Inventée en 1955 pour décrire une sous-discipline de l’informatique, l’intelligence artificielle comprend aujourd’hui une variété de technologies et d’outils, certains plus anciens que d’autres. Forrester a récemment publié un rapport TechRadar sur l’intelligence artificielle (destiné aux professionnels du développement d’applications), une analyse détaillée de 13 technologies que les entreprises devraient songer à adopter afin d’épauler et de soutenir les décisions des humains, voici le top des 10 meilleures technologies de l’IA :
Génération automatique de texte : Production de texte à partir de données informatiques. Actuellement utilisé dans les services à la clientèle, la génération de rapports et la synthèse de business intelligence. Exemples de fournisseurs: Attivio, Cambridge Semantics, Raisonnement numérique, Lucidworks, Narrative Science, SAS, Yseop.
Reconnaissance automatique de la parole : Transcrire et transformer la parole humaine en format utile pour les applications informatiques. Actuellement utilisée dans les systèmes interactifs de réponse vocale et les applications mobiles. Exemples de fournisseurs : NICE, Nuance Communications, OpenText, Verint Systems.
Agents virtuels. De simples chatbots à des systèmes avancés qui peuvent communiquer avec les humains. Actuellement utilisés dans les services à la clientèle et comme gestionnaires de maison intelligente. Exemples de fournisseurs : Amazon, Apple, Solutions Artificielles, Assist AI, Creative Virtual, Google, IBM, IPsoft, Microsoft, Satisfi. Plateformes d’apprentissage automatique : Fourniture d’algorithmes, d’API, de boîtes à outils de développement et de formation, de données, ainsi qu’une puissance de calcul pour concevoir, former et déployer des modèles dans des applications, des processus et autres machines. Actuellement utilisées dans un large éventail d’applications d’entreprise, impliquant principalement la prédiction ou la classification. Exemples de fournisseurs : Amazon, Fractal Analytics, Google, H2O.ai, Microsoft, SAS, Skytree.
Matériel optimisé pour l’IA : Processeurs graphiques et appareils spécialement designés et conçus pour exécuter efficacement des travaux informatiques orientés vers l’IA. Exemples de fournisseurs : Alluviate, Cray, Google, IBM, Intel, Nvidia.
Aide à la décision : Moteurs qui insèrent règles et logique dans les systèmes d’IA, utilisée pour la configuration, la maintenance et les réglages. Une technologie mature, employée par une grande variété d’applications d’entreprise, d’assistance ou de prise de décision automatisée. Exemples de fournisseurs : Concepts de systèmes avancés, Informatica, Maana, Pegasystems, UiPath. Apprentissage profond : Un type particulier d’apprentissage automatique composé de réseaux neuronaux artificiels. Actuellement, il est principalement utilisé dans les applications de reconnaissance de formes et de classification, soutenues par une très grande base de données. Exemples de fournisseurs : Deep Instinct, Ersatz Labs, Fluid AI, MathWorks, Peltarion, Saffron Technology, Sentient Technologies. Reconnaissance biométrique : Permet des interactions plus naturelles entre les humains et les machines, y compris, mais sans s’y limiter, l’image et la reconnaissance tactile, la parole et le langage corporel. Principalement utilisée dans les études de marché. Exemples de fournisseurs : 3VR, Affectiva, Agnitio, FaceFirst, Sensory, Synqera, Tahzoo.
Automatisation robotisée : Utilisation de scripts et autres méthodes pour automatiser l’action humaine, afin de prendre efficacement en charge certains métiers. Actuellement utilisée là où il est trop cher ou inefficace pour les humains d’exécuter une tâche ou un processus. Exemples de fournisseur s: Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, WorkFusion. Fouille de textes et TALN : Le traitement automatique du langage naturel (TALN) utilise et soutient l’analyse du texte en facilitant la compréhension de la structure et de la signification des phrases, du sentiment et de l’intention par des méthodes statistiques et d’apprentissage automatique. Actuellement utilisés dans la détection de fraude, la sécurité, les assistants automatisés, et des applications pour l’exploitation de données non structurées. Exemples de fournisseurs : Basis Technology, Coveo, Expert System, Indico, Knime, Lexalytics, Linguamatics, Mindbreeze, Sinequa, Stratifyd, Synapsify.
Aujourd’hui l’IA offre de nombreux avantages pour le développement des entreprises, mais selon un sondage mené en 2016 par Forrester, quelques obstacles barrent encore la route à l’adoption de ces technologies par ces dernières, freinant ainsi leurs investissements.
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OpenText reveals 2024 nastiest malware, LockBit leads list
http://i.securitythinkingcap.com/TG6JpK
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New Trends of Web Content Management Market Size, Share, Demand, Outlook, Advance Technology And Forecast -2029
Adobe (US), OpenText (Canada), Microsoft (US), Oracle (US), Automattic (US), RWS (UK), Progress (US), OpenAI (US), Canva (US), Upland Software (US), Yext (US), HubSpot (US), HCL Technologies (India), Sitecore (US), Acquia (US), Optimizely (US), Bloomreach (US), Lumen Technologies (US), Contentful (Germany), Pantheon (US), ContentStack (US). Web Content Management (WCM) Market by Product Type…
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AI and Automation Transforming Quality Engineering: Insights from the 2024 World Quality Report
New Post has been published on https://thedigitalinsider.com/ai-and-automation-transforming-quality-engineering-insights-from-the-2024-world-quality-report/
AI and Automation Transforming Quality Engineering: Insights from the 2024 World Quality Report
The World Quality Report 2024-25 by OpenText sheds light on groundbreaking trends shaping Quality Engineering (QE) and testing practices globally. With over 1,775 executives surveyed across 33 countries, the report uncovers how AI, automation, and sustainability are transforming the landscape of quality assurance. As AI technology progresses, organizations are being called to adopt new, innovative solutions for QE, especially as Generative AI (Gen AI) takes center stage.
We will explore the report’s findings, emphasizing key trends in QE, automation, and AI, and providing actionable insights for organizations ready to embrace the future of quality engineering.
The Rise of AI in Quality Engineering
One of the report’s least striking revelations is the rapid adoption of AI in QE. A staggering 71% of organizations have integrated AI and Gen AI into their operations, up from 34% in previous years. This shift marks a pivotal moment in the industry, with AI set to revolutionize various aspects of QE, from test automation to data quality management.
AI’s impact is particularly profound in test automation, where 73% of respondents cite AI and machine learning (ML) as key drivers of progress. Cloud-native technologies and robotic process automation (RPA) follow closely behind, with 67% and 66%, respectively, leveraging these advancements. The speed and efficiency of automation are improving dramatically, allowing organizations to reduce manual efforts and increase testing scope.
For instance, 72% of organizations report that Gen AI has accelerated their test automation processes, while 68% highlight easier integrations, enabling a seamless fit into existing development pipelines. By automating repetitive tasks and generating test scripts, AI is not only reducing costs but also enhancing the productivity of quality engineers.
Quality Engineering in Agile: A Shift Towards Integrated Teams
The growing importance of embedding QE into Agile teams is another major trend highlighted by the report. Currently, 40% of organizations have quality engineers integrated directly into their Agile workflows. This shift is a clear move away from traditional Testing Centers of Excellence (TCoEs), which have declined in use, now comprising only 27% of respondents’ QE structures, compared to a staggering 70% in previous years.
The focus on embedding QE within Agile teams ensures faster iterations and better alignment with business goals. Furthermore, cross-functional collaboration is recognized as critical for delivering higher-quality results, with 78% of respondents emphasizing its importance in ensuring better quality products faster.
Despite these advances, challenges remain. The report finds that 56% of organizations still view QE as a non-strategic function, and 53% acknowledge that their current QE processes are insufficient for Agile methodologies. This calls for a more significant focus on aligning QE metrics with broader business outcomes, such as customer satisfaction and revenue impact.
Data Quality: The Foundation for AI-Driven Testing
As organizations become more reliant on data-driven decision-making, the quality of their data takes on heightened importance. The report reveals that 64% of organizations now consider data quality a top priority, but many are still grappling with how to effectively manage it. Establishing clear ownership of data and improving frameworks for data governance are essential steps toward ensuring the accuracy and reliability of AI models used in QE.
Without high-quality data, AI’s ability to generate meaningful insights, create test scenarios, and predict outcomes is compromised. This explains why 58% of respondents rank data breaches as the most significant risk associated with Gen AI. As organizations integrate AI into their quality processes, ensuring robust data security becomes paramount.
Intelligent Product Validation: Testing Beyond Functionality
The validation of intelligent products is emerging as a critical component of modern QE practices. According to the report, 21% of testing budgets are now dedicated to validating smart technologies, reflecting the growing need for comprehensive strategies to ensure these products perform seamlessly in interconnected environments.
Functional correctness remains the top priority for validating intelligent products, with 30% of respondents citing it as the most important factor. However, security (23%) and data quality (21%) also rank highly, signaling a shift toward more holistic testing strategies that address the complexity of smart products.
The report also identifies challenges in testing these products, particularly when it comes to the validation of embedded AI models and the ability to test all integrations across devices and protocols. A lack of skilled testers further exacerbates these challenges, with 44% of organizations struggling to find talent capable of handling the intricacies of intelligent product testing.
Sustainability in Quality Engineering
With the rising concerns over climate change and environmental responsibility, 58% of organizations are prioritizing sustainability within their QE strategies. However, only 34% have implemented practices that measure the environmental impact of their testing activities. This highlights a significant gap between intent and execution, underscoring the need for more robust frameworks to track sustainability efforts.
Organizations are beginning to explore how QE can contribute to Green IT initiatives, with areas such as energy consumption monitoring, environmental data analysis, and optimization of test environments gaining traction. AI can play a pivotal role in these efforts, with 54% of respondents identifying energy efficiency optimization as one of the most valuable uses of AI in quality validation.
Key Recommendations for the Future
The report offers several key recommendations for organizations looking to stay competitive in the evolving QE landscape:
Leverage Gen AI for Automation: Start experimenting with Gen AI to enhance and accelerate test automation processes. Gen AI’s potential extends beyond script generation, offering opportunities for self-adaptive automation systems that can boost both efficiency and effectiveness.
Invest in QE Talent: To keep pace with AI and automation, organizations must invest in upskilling their quality engineers. Full-stack engineers, capable of working across the entire software lifecycle, are increasingly in demand.
Focus on Business Performance Metrics: Shift away from traditional metrics like process efficiency and test coverage. Instead, focus on how QE initiatives contribute to business outcomes, such as customer satisfaction and revenue growth.
Develop a Sustainability Strategy: Implement comprehensive processes to measure and reduce the environmental impact of QE activities. Integrating sustainability into testing will not only advance corporate social responsibility goals but also improve operational efficiency.
Conclusion
The World Quality Report 2024-25 paints a vivid picture of an industry on the cusp of transformation, driven by AI, automation, and sustainability. As organizations navigate this new landscape, adopting a forward-thinking approach to QE will be essential to gaining a competitive edge. By leveraging AI’s potential, investing in talent, and aligning quality initiatives with business goals, companies can ensure they are prepared for the challenges and opportunities that lie ahead.
#2024#adoption#agile#ai#AI models#Analysis#approach#automation#budgets#Business#business goals#change#climate#climate change#Cloud#Cloud-Native#Collaboration#Companies#complexity#comprehensive#data#data analysis#Data Breaches#Data Governance#data quality#data quality management#data security#data-driven#development#devices
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26 ألف عميل من مستخدمي الإنترنت فى بنك تنمية الصادرات E- bank
أعلن بنك تنمية الصادرات E- bank عن أرتفاع عدد مستخدمي الإنترنت البنكي إلى 26.249 ألف عميل من أصل 25 ألف عميل مستهدف، مشيراً أيضاً إلى أرتفاع عدد المحافظ الإلكترونية ليسجل 23.672 ألف محفظة من إجمالي مستهدف 30 ألف محفظة إلكترونية. وفى سياق متصل، أعلنت شركة OpenText، أن البنك المصري لتنمية الصادرات قد عزز كفاءته التشغيلية من خلال الإستفاده من OpenText IT Operations Management بتقديم حلول مبتكره و…
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IQBGinc the OpenText records management platform has been designed to provide the smallest incremental cost and quickest time to production. For more info please visit our website.
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OpenText Introduces AI-Powered Code Security Innovation to Empower DevSecOps Teams http://dlvr.it/T9jxjK
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OpenText Fortify Aviator integrates SAST more closely into developer workflows
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