Adopting a Next Generation Data Security Strategy

This white paper highlights how organizations can adopt a next generation data security strategy that bridges security technologies deployed across heterogeneous and highly distributed environments. Organizations are lacking a centralized view of their data security risk posture, compounded by the complexity of managing security across distributed environments. This lack of visibility results in an ineffective way of prioritizing alerts and assessing the business impact of lost or stolen data assets. Taking a holistic approach affords organizations a comprehensive view of existing security risks to sensitive data.

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Adopting a Next Generation Data Security Strategy

This white paper highlights how organizations can adopt a next generation data security strategy that bridges security technologies deployed across heterogeneous and highly distributed environments. Organizations are lacking a centralized view of their data security risk posture, compounded by the complexity of managing security across distributed environments. This lack of visibility results in an ineffective way of prioritizing alerts and assessing the business impact of lost or stolen data assets. Taking a holistic approach affords organizations a comprehensive view of existing security risks to sensitive data.

View Now

Adopting a Next Generation Data Security Strategy

This white paper highlights how organizations can adopt a next generation data security strategy that bridges security technologies deployed across heterogeneous and highly distributed environments. Organizations are lacking a centralized view of their data security risk posture, compounded by the complexity of managing security across distributed environments. This lack of visibility results in an ineffective way of prioritizing alerts and assessing the business impact of lost or stolen data assets. Taking a holistic approach affords organizations a comprehensive view of existing security risks to sensitive data.

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AI Transformation Playbook

AI (Artificial Intelligence) technology is now poised to transform every industry, just as electricity did 100 years ago. Between now and 2030, it will create an estimated $13 trillion of GDP growth. While it has already created tremendous value in leading technology companies such as Google, Baidu, Microsoft and Facebook, much of the additional waves of value creation will go beyond the software sector.

This AI Transformation Playbook draws on insights gleaned from leading the Google Brain team and the Baidu AI Group, which played leading roles in transforming both Google and Baidu into great AI companies. It is possible for any enterprise to follow this Playbook and become a strong AI company, though these recommendations are tailored primarily for larger enterprises with a market cap/valuation from $500M to $500B.

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Redefining Quality Control with AI-powered Visual Inspection for Manufacturing

Emerging technology — from the introduction of assembly lines to the Internet of Things — has always defined manufacturing.

With the creation of computers and early automation came traditional machine vision, in which machines analyze photos of parts and components for defects based on a set of human-defined rules. While it reduces human error, traditional machine vision lacks the capacity to solve for pain points like complex defects and changing environments.

Today, more sophisticated artificial intelligence (AI), including machine learning (ML) and deep learning (DL), allows manufacturers to use AI-powered visual inspection to enhance quality and reduce costs. But even now, only 5% of manufacturing companies have a clearly defined strategy for implementing AI.

Companies need strategies to overcome challenges in visual inspection, which still relies heavily on human inspectors or inflexible rules-based machine vision. The cost of sending defective pieces to customers — both in reputation and in recalls — isn’t sustainable in a competitive global environment.

The right AI platforms offer tools that can enhance quality control and cut costs — after users tackle key obstacles.

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Accelerate AI Adoption

Landing AI’s industrial AI platform consists of a suite of interconnected tools that enables you to build, deploy, manage and scale AI solutions for visual inspection in an end-to-end workflow.

Designed from the bottom up to enable manufacturers to take projects from concepts to scalable solutions with speed, LandingLens minimizes customization and scaling challenges. While AI models are unique, leveraging universal tools can expedite complex projects. Built for evolving data, LandingLens is comprised of a suite of tools to automate machine learning for industrial vision.

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Drive Better Business Outcomes

Any downtime caused by poor database performance interrupts business operations, has a negative impact on productivity, and can directly affect the bottom line. And enterprise applications like SQL Server are the backbone of any organization.

Read our whitepaper to see how you can ensure your organization is operating at peak performance by applying comprehensive monitoring to improve business outcomes.

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Manage the Multiple Database Journey

To ensure adequate transactional capacity, most enterprises have adopted a multi-database strategy—using several different database platforms to store different classes or categories of data. So, there’s been a surge in the number of databases in use at most organizations, with database managers increasingly responsible for numerous instances.

In the multi-database environment, ensuring each individual database operates at its optimal level is critical. And since database platforms don’t all operate the same way, database managers must gain expertise on the multiple platforms. They also must continue to conduct performance tuning, maintain high availability, and ensure data security—again for multiple platforms.

Read our whitepaper to see how your business can best manage multiple databases.

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Adopting a Next Generation Data Security Strategy

This white paper highlights how organizations can adopt a next generation data security strategy that bridges security technologies deployed across heterogeneous and highly distributed environments. Organizations are lacking a centralized view of their data security risk posture, compounded by the complexity of managing security across distributed environments. This lack of visibility results in an ineffective way of prioritizing alerts and assessing the business impact of lost or stolen data assets. Taking a holistic approach affords organizations a comprehensive view of existing security risks to sensitive data.

View Now

10 reasons to run SAP S/4HANA on Red Hat Enterprise Linux

Choose an infrastructure platform that lets you optimize your SAP environment and operations while preparing you for the future. Through trusted technologies, investment protection, and flexible innovation, Red Hat can help you modernize your SAP systems and build a foundation for digital transformation.

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The Changing Landscape of B2B Commerce

B2B Commerce is quickly evolving, with customers expecting more, but the technology has drastically improved, making delivering on such expectations simpler. Learn how to leverage best practices and modern technology to make your B2B eCommerce website fresh and relevant for your customers today.

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