In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
In this webinar, we’ll show you how Cloudera SDX reduces the complexity in your data management environment and lets you deliver diverse analytics with consistent security, governance, and lifecycle management against a shared data catalog.
Get started with Cloudera's cyber solutionCloudera, Inc.
Cloudera empowers cybersecurity innovators to proactively secure the enterprise by accelerating threat detection, investigation, and response through machine learning and complete enterprise visibility. Cloudera’s cybersecurity solution, based on Apache Spot, enables anomaly detection, behavior analytics, and comprehensive access across all enterprise data using an open, scalable platform. But what’s the easiest way to get started?
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
Cloudera - The Modern Platform for AnalyticsCloudera, Inc.
This presentation provides an overview of Cloudera and how a modern platform for Machine Learning and Analytics better enables a data-driven enterprise.
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.
Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Introducing Cloudera Data Science Workbench for HDP 2.12.19Cloudera, Inc.
Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.
The document outlines the agenda for Cloudera's Enterprise Data Cloud event in Vienna. It includes welcome remarks, keynotes on Cloudera's vision and customer success stories. There will be presentations on the new Cloudera Data Platform and customer case studies, followed by closing remarks. The schedule includes sessions on Cloudera's approach to data warehousing, machine learning, streaming and multi-cloud capabilities.
Consolidate your data marts for fast, flexible analytics 5.24.18Cloudera, Inc.
In this webinar, Cloudera and AtScale will showcase:
How a company can modernize their analytic architecture to deliver flexibility and agility to more end-users.
How using AtScale’s Universal Semantic layer can end the data chaos and allow business users to use the data in the modern platform.
Highlight the performance of AtScale and Cloudera’s analytic database with newly completed TPC-DS standard benchmarking.
Best practices for migrating from legacy appliances.
How komatsu is driving operational efficiencies using io t and machine learni...Cloudera, Inc.
In this joint webinar, Jason Knuth, data scientist and analytics lead at Komatsu shares how they are analyzing over 17 billion data points every day from connected devices and using machine learning and analytics to improve mining operations.
The 6th Wave of Automation: Automation of Decisions | Cloudera Analytics & Ma...Cloudera, Inc.
This presentation provides detail on how we are now in the 6th wave of automation, that is based on Machine Learning. In this 6th wave, Cloudera plays a critical role in providing the data platform for Machine Learning and Analytics built for the Cloud.
Turning Data into Business Value with a Modern Data PlatformCloudera, Inc.
The document discusses how data has become a strategic asset for businesses and how a modern data platform can help organizations drive customer insights, improve products and services, lower business risks, and modernize IT. It provides examples of companies using analytics to personalize customer solutions, detect sepsis early to save lives, and protect the global finance system. The document also outlines the evolution of Hadoop platforms and how Cloudera Enterprise provides a common workload pattern to store, process, and analyze data across different workloads and databases in a fast, easy, and secure manner.
Big data journey to the cloud maz chaudhri 5.30.18Cloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
How to Build Multi-disciplinary Analytics Applications on a Shared Data PlatformCloudera, Inc.
The document discusses building multi-disciplinary analytics applications on a shared data platform. It describes challenges with traditional fragmented approaches using multiple data silos and tools. A shared data platform with Cloudera SDX provides a common data experience across workloads through shared metadata, security, and governance services. This approach optimizes key design goals and provides business benefits like increased insights, agility, and decreased costs compared to siloed environments. An example application of predictive maintenance is given to improve fleet performance.
Preparing data for analysis and insights is the foundation of any data-driven exercise. Moving workloads to a PaaS, be it data engineering, analytic database, or data science requires a two step leap of faith - in trusting the public cloud, and then your PaaS vendor. In this webinar we will discuss the architecture of a PaaS solution for data management and understand the nitty gritty details of what exactly this involves with the following:
An exploration of the architecture of Cloudera Altus PaaS - the industry’s first multi-function, multi-cloud data and analytic platform-as-a-service
A dive into use cases and a demo of Altus
The synergy between AWS and Altus to help you securely standardize on a combination of public cloud and data management
3 things to learn:
An exploration of the architecture of Cloudera Altus PaaS - the industry’s first multi-function, multi-cloud data and analytic platform-as-a-service
A dive into use cases and a demo of Altus
The synergy between AWS and Altus to help you securely standardize on a combination of public cloud and data management
Introducing Cloudera DataFlow (CDF) 2.13.19Cloudera, Inc.
Watch this webinar to understand how Hortonworks DataFlow (HDF) has evolved into the new Cloudera DataFlow (CDF). Learn about key capabilities that CDF delivers such as -
-Powerful data ingestion powered by Apache NiFi
-Edge data collection by Apache MiNiFi
-IoT-scale streaming data processing with Apache Kafka
-Enterprise services to offer unified security and governance from edge-to-enterprise
Part 1: Cloudera’s Analytic Database: BI & SQL Analytics in a Hybrid Cloud WorldCloudera, Inc.
3 Things to Learn About:
* On-premises versus the cloud: What’s the same and what’s different?
* Design and benefits of analytics in the cloud
* Best practices and architectural considerations
Spark and Deep Learning Frameworks at Scale 7.19.18Cloudera, Inc.
We'll outline approaches for preprocessing, training, inference, and deployment across datasets (time series, audio, video, text, etc.) that leverage Spark, along with its extended ecosystem of libraries and deep learning frameworks using Cloudera's Data Science Workbench.
Building a Data Hub that Empowers Customer Insight (Technical Workshop)Cloudera, Inc.
We have seen the evolution with the Bi and Data Science fields from the structured data warehouse to data lake and finally, to the data hub. This session will cover the key steps required to building a data hub, examining how best to align and engage stakeholders and develop architectural sanction to enable your organisations to realise new customer insights and better enable you to achieve business objectives.
Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...Cloudera, Inc.
For self-service BI and exploratory analytic workloads, the cloud can provide a number of key benefits, but the move to the cloud isn’t all-or-nothing. Gartner predicts nearly 80 percent of businesses will adopt a hybrid strategy. Learn how a modern analytic database can power your business-critical workloads across multi-cloud and hybrid environments, while maintaining data portability. We'll also discuss how to best leverage the increased agility cloud provides, while maintaining peak performance.
Cloudera Altus: Big Data in the Cloud Made EasyCloudera, Inc.
Cloudera Altus makes it easier for data engineers, ETL developers, and anyone who regularly works with raw data to process that data in the cloud efficiently and cost effectively. In this webinar we introduce our new platform-as-a-service offering and explore challenges associated with data processing in the cloud today, how Altus abstracts cluster overhead to deliver easy, efficient data processing, and unique features and benefits of Cloudera Altus.
The 5 Biggest Data Myths in Telco: ExposedCloudera, Inc.
The document discusses common myths in the telecommunications industry regarding big data and analytics. It addresses five myths: 1) that data is too diverse to analyze, 2) that open source means open security, 3) that big data platforms do not provide adequate return on investment, 4) that big data tools are too difficult for teams to learn, and 5) that legacy systems cannot handle additional data solutions. For each myth, it provides facts and examples to demonstrate why the myths are unfounded and how organizations can leverage big data to drive insights.
Making Self-Service BI a Reality in the EnterpriseCloudera, Inc.
For most analysts, the pace of analytics and data science can be frustrating. The common waterfall approach works well for the fixed reports, but it can be a lengthy process to request additional data sets, create new reports, or serve new use cases. So it’s no surprise that organizations are looking to shift towards a self-service model, empowering business users to discover and iterate quickly.
However, it’s not just about opening up this access, but also ensuring the results are accurate and trusted. When there are petabytes of data, how does a user know which tables to use and which are most relevant? How do you strike the balance between discovery and agility, while still meeting enterprise governance standards to truly get more value from your data?
During this webinar, you’ll learn how to empower end-users to make self-service BI a reality within your organization while fostering governance collaboration between all data stakeholders. We’ll discuss and demo:
Strategies of consolidating data across silos for fast, flexible access
Enabling easy discovery and exploration, including understanding which data to trust and where to start
New capabilities for intelligent query assistance as well as immediate performance optimizations and recommendations as-you-go
Collaboration and access outside of just SQL for data science and beyond
In addition, we will walk through best practices and considerations when developing your organizational strategy around self-service analytics, and highlight several real-world success stories from a wide range of industries.
3 things to learn:
Strategies of consolidating data across silos for fast, flexible access
Enabling easy discovery and exploration, including understanding which data to trust and where to start
New capabilities for intelligent query assistance as well as immediate performance optimizations and recommendations as-you-go
Capgemini Leap Data Transformation Framework with ClouderaCapgemini
https://www.capgemini.com/insights-data/data/leap-data-transformation-framework
The complexity of moving existing analytical services onto modern platforms like Cloudera can seem overwhelming. Capgemini’s Leap Data Transformation Framework helps clients by industrializing the entire process of bringing existing BI assets and capabilities to next-generation big data management platforms.
During this webinar, you will learn:
• The key drivers for industrializing your transformation to big data at all stages of the lifecycle – estimation, design, implementation, and testing
• How one of our largest clients reduced the transition to modern data architecture by over 30%
• How an end-to-end, fact-based transformation framework can deliver IT rationalization on top of big data architectures
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the CloudCloudera, Inc.
3 Things to Learn About:
*On-premises versus the cloud
*Design & benefits of real-time operational data in the cloud
*Best practices and architectural considerations
This document discusses big data and Cloudera's Enterprise Data Hub solution. It begins by noting that big data is growing exponentially and now includes structured, complex, and diverse data types from various sources. Traditional data architectures using relational databases cannot effectively handle this scale and variety of big data. The document then introduces Cloudera's Hadoop-based Enterprise Data Hub as an open, scalable, and cost-effective platform that can ingest and process all data types and bring compute capabilities to the data. It provides an overview of Cloudera's history and product offerings that make up its full big data platform.
Building a Modern Analytic Database with Cloudera 5.8Cloudera, Inc.
This document discusses building a modern analytic database with Cloudera. It outlines Marketing Associates' evaluation of solutions to address challenges around managing massive and diverse data volumes. They selected Cloudera Enterprise to enable self-service BI and real-time analytics at lower costs than traditional databases. The solution has provided scalability, cost savings of over 90%, and improved security and compliance. Future roadmaps for Cloudera's analytic database include faster SQL, improved multitenancy, and deeper BI tool integration.
This document discusses Cloudera's big data solutions and provides examples of how organizations have used Cloudera to optimize data and achieve business goals. It highlights Cloudera's large partner ecosystem and customer base across various industries. Specific use cases are presented on customer experience management, network optimization, and operational analytics. The document promotes Cloudera as enabling data-driven decisions, improved efficiencies, and new business opportunities through modern data architectures.
The Future of Data Management: The Enterprise Data HubCloudera, Inc.
The document discusses the enterprise data hub (EDH) as a new approach for data management. The EDH allows organizations to bring applications to data rather than copying data to applications. It provides a full-fidelity active compliance archive, accelerates time to insights through scale, unlocks agility and innovation, consolidates data silos for a 360-degree view, and enables converged analytics. The EDH is implemented using open source, scalable, and cost-effective tools from Cloudera including Hadoop, Impala, and Cloudera Manager.
Manufacturers have an abundance of data, whether from connected sensors, plant systems, manufacturing systems, claims systems and external data from industry and government. Manufacturers face increased challenges from continually improving product quality, reducing warranty and recall costs to efficiently leveraging their supply chain. For example, giving the manufacturer a complete view of the product and customer information integrating manufacturing and plant floor data, with as built product configurations with sensor data from customer use to efficiently analyze warranty claim information to reduce detection to correction time, detect fraud and even become proactive around issues requires a capable enterprise data hub that integrates large volumes of both structured and unstructured information. Learn how an enterprise data hub built on Hadoop provides the tools to support analysis at every level in the manufacturing organization.
MongoDB IoT City Tour STUTTGART: Hadoop and future data management. By, ClouderaMongoDB
Bernard Doering, Senior Slaes Director DACH, Cloudera.
Hadoop and the Future of Data Management. As Hadoop takes the data management market by storm, organisations are evolving the role it plays in the modern data centre. Explore how this disruptive technology is quickly transforming an industry and how you can leverage it today, in combination with MongoDB, to drive meaningful change in your business.
Turning Petabytes of Data into Profit with Hadoop for the World’s Biggest Ret...Cloudera, Inc.
PRGX is the world's leading provider of accounts payable audit services and works with leading global retailers. As new forms of data started to flow into their organizations, standard RDBMS systems were not allowing them to scale. Now, by using Talend with Cloudera Enterprise, they are able to acheive a 9-10x performance benefit in processing data, reduce errors, and now provide more innovative products and services to end customers.
Watch this webinar to learn how PRGX worked with Cloudera and Talend to create a high-performance computing platform for data analytics and discovery that rapidly allows them to process, model, and serve massive amount of structured and unstructured data.
The Future of Data Management: The Enterprise Data HubCloudera, Inc.
The document discusses the future of data management through the use of an enterprise data hub (EDH). It notes that an EDH provides a centralized platform for ingesting, storing, exploring, processing, analyzing and serving diverse data from across an organization on a large scale in a cost effective manner. This approach overcomes limitations of traditional data silos and enables new analytic capabilities.
Keynote from Big Data World Show Singapore, April 2015.
• How is data driving change?
• Where are the opportunities, across industries?
• What is required to gain value from data?
• How can you get started today?
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondCloudera, Inc.
Federal organizations increasingly are focused on creating environments that enable more data-driven decisions. Yet ensuring that all data is considered and is current, complete, and accurate is a tall order for most. To make data analytics meaningful to support real-world transformation, agency staff need business tools that provide user-friendly dashboards, on-demand reporting, and methods to manage efficiently the rise of voluminous and varied data sets and types commonly associated with big data. In most cases, existing systems are insufficient to support these requirements. Enter the enterprise data hub (EDH), a software architecture specifically designed to be a unified platform that can economically store unlimited data and enable diverse access to it at scale. Plan to attend this discussion to understand the key considerations to making an EDH the architectural center of your agency’s modern data strategy.
Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...Cloudera, Inc.
Maschinelles Lernen und Analyseanwendungen explodieren im Unternehmen und ermöglichen Anwendungsfällen in Bereichen wie vorbeugende Wartung, Bereitstellung neuer, wünschenswerter Produktangebote für Kunden zum richtigen Zeitpunkt und Bekämpfung von Insider-Bedrohungen für Ihr Unternehmen.
Optimize your cloud strategy for machine learning and analyticsCloudera, Inc.
Join industry superstars Mike Olson (Cloudera CSO and co-founder) and Jim Curtis (451 Research senior analyst) as they outline the best practices for cloud-based machine learning and analytics in this “can’t miss” webinar.
Hot topics include:
Why enterprises are moving their analytics to the public cloud
How to select the best cloud deployment model
Design tricks that make cloud economics work
Success stories, cautionary tales, and lessons learned
James will share 451 Research findings and offer insights learned from surveying both the vendor landscape and enterprise practitioners.
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Mike will regale you with his vision for the future of multi-disciplinary machine learning and analytics in hybrid- and multi-cloud environments
3 things to learn:
Why enterprises are moving their analytics to the public cloud
How to select the best cloud deployment model
Design tricks that make cloud economics work
Similar to Data Driven With the Cloudera Modern Data Warehouse 3.19.19 (20)
The document discusses using Cloudera DataFlow to address challenges with collecting, processing, and analyzing log data across many systems and devices. It provides an example use case of logging modernization to reduce costs and enable security solutions by filtering noise from logs. The presentation shows how DataFlow can extract relevant events from large volumes of raw log data and normalize the data to make security threats and anomalies easier to detect across many machines.
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
The document outlines the 2021 finalists for the annual Data Impact Awards program, which recognizes organizations using Cloudera's platform and the impactful applications they have developed. It provides details on the challenges, solutions, and outcomes for each finalist project in the categories of Data Lifecycle Connection, Cloud Innovation, Data for Enterprise AI, Security & Governance Leadership, Industry Transformation, People First, and Data for Good. There are multiple finalists highlighted in each category demonstrating innovative uses of data and analytics.
Machine Learning with Limited Labeled Data 4/3/19Cloudera, Inc.
Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.
Join Cloudera Fast Forward Labs Research Engineer, Mike Lee Williams, to hear about their latest research report and prototype on Federated Learning. Learn more about what it is, when it’s applicable, how it works, and the current landscape of tools and libraries.
Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.
451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
Cloudera's big data platform can help organizations comply with the EU's General Data Protection Regulation (GDPR) in three key ways:
1. It provides a single system to securely store, govern, and manage all analytic workloads and personal data across on-premises, cloud, structured, and unstructured data sources.
2. Its shared services like data catalog, security, governance, and lifecycle management can be applied uniformly across the platform to meet GDPR principles like data minimization, storage limitation, and accuracy.
3. Specific capabilities like its GDPR data hub, consent management, and ability to delete individual data records upon request help automate key GDPR requirements at scale,
To disrupt and innovate, you need access to data. All of your data. The challenge for many organisations is that the data they need is locked away in a variety of silos. And there's perhaps no bigger silo than one of the most a widely deployed business application: SAP. Bringing together all your data for analytics and machine learning unlocks new insights and business value. Together, Cloudera and Datavard hold the key to breaking SAP data out of its silo, providing access to unlimited and untapped opportunities that currently lay hidden.
Multi task learning stepping away from narrow expert models 7.11.18Cloudera, Inc.
Join this webinar as Friederike Schüür covers:
A conceptual introduction to multi-task learning (MTL), how and why it works
A technical deep dive, from MTL random forests to MTL neural networks
Applications of MTL, from structured data to text and images
The benefits of MTL to organizations, from financial services to healthcare and agriculture
Cloudera training secure your cloudera cluster 7.10.18Cloudera, Inc.
Exclusively through Cloudera OnDemand, Cloudera Security Training introduces you to the tools and techniques that Cloudera's solution architects use to protect the clusters our customers rely on for critical machine learning and analytics workloads. This webinar will give you a sneak peek at our new on-demand security course and show you the immense scope of Cloudera training. From authentication and authorization to encryption, auditing, and everything in between, this course gives you the skills you need to properly secure your Cloudera cluster.
Delivering improved patient outcomes through advanced analytics 6.26.18Cloudera, Inc.
Rush University Medical Center, along with Cloudera and MetiStream, talk about adopting a comprehensive and interactive analytic platform for improved patient outcomes and better genomic analysis, highlighting examples in both genomics and clinical notes. John Spooner of 451 Research provides context to the discussion and shares market insights that complement the customer stories.
Redefining Cybersecurity with AI CapabilitiesPriyanka Aash
In this comprehensive overview of Cisco's latest innovations in cybersecurity, the focus is squarely on resilience and adaptation in the face of evolving threats. The discussion covers the imperative of tackling Mal information, the increasing sophistication of insider attacks, and the expanding attack surfaces in a hybrid work environment. Emphasizing a shift towards integrated platforms over fragmented tools, Cisco introduces its Security Cloud, designed to provide end-to-end visibility and robust protection across user interactions, cloud environments, and breaches. AI emerges as a pivotal tool, from enhancing user experiences to predicting and defending against cyber threats. The blog underscores Cisco's commitment to simplifying security stacks while ensuring efficacy and economic feasibility, making a compelling case for their platform approach in safeguarding digital landscapes.
"Hands-on development experience using wasm Blazor", Furdak Vladyslav.pptxFwdays
I will share my personal experience of full-time development on wasm Blazor
What difficulties our team faced: life hacks with Blazor app routing, whether it is necessary to write JavaScript, which technology stack and architectural patterns we chose
What conclusions we made and what mistakes we committed
The Challenge of Interpretability in Generative AI Models.pdfSara Kroft
Navigating the intricacies of generative AI models reveals a pressing challenge: interpretability. Our blog delves into the complexities of understanding how these advanced models make decisions, shedding light on the mechanisms behind their outputs. Explore the latest research, practical implications, and ethical considerations, as we unravel the opaque processes that drive generative AI. Join us in this insightful journey to demystify the black box of artificial intelligence.
Dive into the complexities of generative AI with our blog on interpretability. Find out why making AI models understandable is key to trust and ethical use and discover current efforts to tackle this big challenge.
TrustArc Webinar - Innovating with TRUSTe Responsible AI CertificationTrustArc
In a landmark year marked by significant AI advancements, it’s vital to prioritize transparency, accountability, and respect for privacy rights with your AI innovation.
Learn how to navigate the shifting AI landscape with our innovative solution TRUSTe Responsible AI Certification, the first AI certification designed for data protection and privacy. Crafted by a team with 10,000+ privacy certifications issued, this framework integrated industry standards and laws for responsible AI governance.
This webinar will review:
- How compliance can play a role in the development and deployment of AI systems
- How to model trust and transparency across products and services
- How to save time and work smarter in understanding regulatory obligations, including AI
- How to operationalize and deploy AI governance best practices in your organization
This PDF delves into the aspects of information security from a forensic perspective, focusing on privacy leaks. It provides insights into the methods and tools used in forensic investigations to uncover and mitigate privacy breaches in mobile and cloud environments.
Discovery Series - Zero to Hero - Task Mining Session 1DianaGray10
This session is focused on providing you with an introduction to task mining. We will go over different types of task mining and provide you with a real-world demo on each type of task mining in detail.
The Zaitechno Handheld Raman Spectrometer is a powerful and portable tool for rapid, non-destructive chemical analysis. It utilizes Raman spectroscopy, a technique that analyzes the vibrational fingerprint of molecules to identify their chemical composition. This handheld instrument allows for on-site analysis of materials, making it ideal for a variety of applications, including:
Material identification: Identify unknown materials, minerals, and contaminants.
Quality control: Ensure the quality and consistency of raw materials and finished products.
Pharmaceutical analysis: Verify the identity and purity of pharmaceutical compounds.
Food safety testing: Detect contaminants and adulterants in food products.
Field analysis: Analyze materials in the field, such as during environmental monitoring or forensic investigations.
The Zaitechno Handheld Raman Spectrometer is easy to use and features a user-friendly interface. It is compact and lightweight, making it ideal for field applications. With its rapid analysis capabilities, the Zaitechno Handheld Raman Spectrometer can help you improve efficiency and productivity in your research or quality control workflows.
Keynote : AI & Future Of Offensive SecurityPriyanka Aash
In the presentation, the focus is on the transformative impact of artificial intelligence (AI) in cybersecurity, particularly in the context of malware generation and adversarial attacks. AI promises to revolutionize the field by enabling scalable solutions to historically challenging problems such as continuous threat simulation, autonomous attack path generation, and the creation of sophisticated attack payloads. The discussions underscore how AI-powered tools like AI-based penetration testing can outpace traditional methods, enhancing security posture by efficiently identifying and mitigating vulnerabilities across complex attack surfaces. The use of AI in red teaming further amplifies these capabilities, allowing organizations to validate security controls effectively against diverse adversarial scenarios. These advancements not only streamline testing processes but also bolster defense strategies, ensuring readiness against evolving cyber threats.
Cracking AI Black Box - Strategies for Customer-centric Enterprise ExcellenceQuentin Reul
The democratization of Generative AI is ushering in a new era of innovation for enterprises. Discover how you can harness this powerful technology to deliver unparalleled customer value and securing a formidable competitive advantage in today's competitive market. In this session, you will learn how to:
- Identify high-impact customer needs with precision
- Harness the power of large language models to address specific customer needs effectively
- Implement AI responsibly to build trust and foster strong customer relationships
Whether you're at the early stages of your AI journey or looking to optimize existing initiatives, this session will provide you with actionable insights and strategies needed to leverage AI as a powerful catalyst for customer-driven enterprise success.
Self-Healing Test Automation Framework - HealeniumKnoldus Inc.
Revolutionize your test automation with Healenium's self-healing framework. Automate test maintenance, reduce flakes, and increase efficiency. Learn how to build a robust test automation foundation. Discover the power of self-healing tests. Transform your testing experience.