Home > News > featured news > Protegrity Adds New Data Protection Platform Features

Data Architecture

Protegrity Adds New Data Protection Platform Features

Protegrity | March 15, 2022

Protegrity, a pioneer in data-centric security, recently launched version 9.0 of the Protegrity Data Protection Platform, which includes enhanced security and data-sharing capabilities to help organizations unleash the full potential of their data in increasingly complex technological contexts. Companies compete on data results, but data security and privacy concerns frequently hinder their ability to compete. New data anonymization features for delivering privacy-enhanced datasets for AI/ML and unified data security for multi-cloud settings to expedite innovation are among the platform upgrades.

With support for leading cloud vendors such as Google Cloud Platform, Microsoft Azure, Amazon Web Services, and Oracle Cloud delivered through a single, streamlined interface, the Protegrity Data Protection Platform enables secure cloud migration, multi-cloud deployments, data sharing, and collaboration. This single end-to-end solution handles data security throughout the company, simplifies security operations, and eliminates the security gaps that arise when data is protected across platforms.

Most businesses keep their data secure in walled gardens (available only to users of a certain platform) that are filled with flaws, complexity, and risk. Protegrity safeguards data wherever it is stored, reducing security risks and ensuring policy compliance.

"Moving to the cloud is essential for businesses to drive continued innovation, yet security concerns and complexity are slowing them from unlocking the full potential of their data. Version 9.0 of the Protegrity Data Protection Platform empowers businesses to make protected data more accessible and productive so that they can capitalize on the power of advanced analytics. When we deliver precise data protection, we alter the enterprise data security model from 'need to know to 'need to share,' unlocking data to deliver greater business value and innovation."

Paul Mountford, CEO, Protegrity

Added Features Are:

  • Unified, Multi-cloud Data Security Empowers Business Resilience and Agility
  • Anonymization Capabilities Deliver Privacy-enhanced, Analytics-ready Data Sets for Advanced Data Collaboration
  • Next-generation Logging Architecture Enables Advanced Threat Hunting

Jeffrey Breen, chief product officer and EVP of product and strategy, Protegrity said that "We've worked closely with our customers to understand their cloud strategies and data security needs to help them unlock the next level of data innovation. The latest release of the Data Protection Platform is a culmination of Protegrity's extensive knowledge and experience in the data protection industry."

Spotlight

Understanding User Entity and Behavior Analytics (UEBA)

User Entity and Behavior Analytics (UEBA) is a cybersecurity technology and approach that focuses on analyzing the behavior of users and entities (such as devices, applications, and systems) within an organization's IT environment. By using advanced data analytics, machine learning algorithms, and artificial intelligence, UEBA aims to detect and prevent cyber threats by identifying anomalies, deviations, or patterns in user and entity activities that might indicate potential security risks.

More featured news

Spotlight

Understanding User Entity and Behavior Analytics (UEBA)

User Entity and Behavior Analytics (UEBA) is a cybersecurity technology and approach that focuses on analyzing the behavior of users and entities (such as devices, applications, and systems) within an organization's IT environment. By using advanced data analytics, machine learning algorithms, and artificial intelligence, UEBA aims to detect and prevent cyber threats by identifying anomalies, deviations, or patterns in user and entity activities that might indicate potential security risks.

Related News

Big Data Management

Cloudera and AWS Enhance Cloud Data Management and Analytics

AWS | September 11, 2023

Cloudera and AWS have signed a strategic collaboration agreement to boost cloud-native data management and analytics. Cloudera, AWS ISV WMP Partner, will use AWS services to innovate and reduce costs with its open data lakehouse. Its Data Platform is engineered to integrate directly with AWS services, providing a cost-effective and innovative platform for customers. Cloudera and Amazon Web Services (AWS) have announced a Strategic Collaboration Agreement (SCA) aimed at bolstering cloud-native data management and analytics. Under this agreement, Cloudera will harness AWS services to provide ongoing innovation and cost reduction to customers using the Cloudera open data lakehouse on AWS for enterprise generative AI. As part of this collaboration, Cloudera, already an AWS Independent Software Vendor (ISV) Workload Migration Program (WMP) Partner, will further simplify workload migration to the cloud and the purchase of Cloudera Data Platform (CDP) on AWS, leveraging AWS Marketplace credits. Cloudera has opted to run key elements of CDP on AWS, including data management, data lakes, data warehouses, operational databases, AI and machine learning, master data management, and security components. This allows customers to transition to CDP in the cloud without the need to refactor their applications, facilitating hybrid deployments. Moreover, Cloudera has designed CDP for seamless integration with various AWS services such as Amazon S3, Amazon EKS, Amazon RDS, and Amazon EC2, delivering a tightly integrated platform that reduces costs and capitalizes on AWS innovations. Customers can access AWS native services without the burden of managing integrations themselves. "Deepening our collaboration with AWS gives customers even more reasons to choose to run the Cloudera Data Platform on AWS. With tighter hardware and AWS service integration, customers get the best possible experience with strong security and governance, along with new cost reduction options to support their most critical analytical workloads, said Paul Codding, Executive Vice President of Product Management, Cloudera. He stated that Cloudera and AWS, when combined, provide organizations with the necessary tools to construct and operate data applications in a manner that can optimally cater to the unique and evolving requirements of their business. [Source: PR Newswire] Beyond technology integration, AWS and Cloudera are set to collaborate on marketing and co-selling programs for customers. The partnership solidifies Cloudera's position as a trusted AWS partner in cloud-native data management and data analytics. "Cloudera has strengthened their collaboration with AWS for shared customers to leverage their existing investments in CDP and accelerate their modernization to the cloud, said Chris Grusz, General Manager, Technology Partnerships and Marketplace at AWS. He mentioned that Cloudera is persistently innovating on AWS throughout its data management platform to deliver authentic data analytics and insights for its customers. [Source: PR Newswire] Cloudera's open data lakehouse approach enables secure data management and portable cloud-native data analytics across various cloud environments, aligning with their mission to make data transformation feasible for the future.

Read More

Big Data Management

IBM Releases Watsonx AI with Generative AI Models for Data Governance

IBM | September 08, 2023

IBM announces plans to enhance its Watsonx AI and data platform, with a focus on scaling AI impact for enterprises. Key improvements include new generative AI models, integration of foundation models, and features like Tuning Studio and Synthetic Data Generator. IBM emphasizes trust, transparency, and governance in training and plans to incorporate AI into its hybrid cloud solutions, although implementation difficulty and cost may be issues. IBM reveals its plans to introduce new generative AI foundation models and enhancements to its Watsonx AI and data platform. The goal is to provide enterprises with the tools they need to scale and accelerate the impact of AI in their operations. These improvements include a technical preview for watsonx.governance, the addition of new generative AI data services to watsonx.data, and the integration of watsonx.ai foundation models into select software and infrastructure products. Developers will have the opportunity to explore these capabilities and models at the IBM TechXchange Conference, scheduled to take place from September 11 to 14 in Las Vegas. The upcoming AI models and features include: 1. Granite Series Models: IBM plans to launch its Granite series models, utilizing the ‘Decoder’ architecture, is essential for large language models (LLMs). These models will support various enterprise natural language processing (NLP) tasks, including summarization, content generation, and insight extraction, with planned availability in Q3 2023. 2. Third-Party Models: IBM is currently offering Meta's Llama 2-chat 70 billion parameter model and the StarCoder LLM for code generation within watsonx.ai on IBM Cloud. IBM places a strong emphasis on trust and transparency in its training process for foundation models. They follow rigorous data collection procedures and include control points to ensure responsible deployments in terms of governance, risk assessment, privacy, bias mitigation, and compliance. IBM also intends to introduce new features across the watsonx platform: For Watsonx.ai: Tuning Studio: IBM plans to release the Tuning Studio, featuring prompt tuning, allowing clients to adapt foundation models to their specific enterprise data and tasks. This is expected to be available in 3Q23. Synthetic Data Generator: IBM has launched a synthetic data generator, enabling users to create artificial tabular data sets for AI model training, reducing risk and accelerating decision-making. For Watsonx.data: Generative AI: IBM aims to incorporate generative AI capabilities into watsonx.data to help users discover, augment, visualize, and refine data for AI through a self-service, natural language interface. This feature is planned for technical preview in 4Q 2023. Vector Database Capability: IBM plans to integrate vector database capabilities into watsonx.data to support watsonx.ai retrieval and augmented generation use cases, also expected in the technical preview in 4Q 2023. For Watsonx.governance: Model Risk Governance for Generative AI: IBM is launching a tech preview for watsonx.governance, providing automated collection and documentation of foundation model details and model risk governance capabilities. Dinesh Nirmal, Senior Vice President, Products, IBM Software, stated that IBM is dedicated to supporting clients throughout the AI lifecycle, from establishing foundational data strategies to model tuning and governance. Additionally, IBM will offer AI assistants to help clients scale AI's impact across various enterprise use cases, such as application modernization, customer care, and HR and talent management. IBM also intends to integrate watsonx.ai innovations into its hybrid cloud software and infrastructure products, including intelligent IT automation and developer services. IBM's upgrades to the Watsonx AI and data platform offer promise but, come with potential drawbacks. Implementation complexity and the need for additional training may create a steep learning curve. The associated costs of advanced technology could be prohibitive for smaller organizations. The introduction of generative AI and synthetic data raises data privacy and security concerns. Additionally, despite efforts for responsible AI, the risk of bias in models necessitates ongoing vigilance to avoid legal and ethical issues.

Read More

Big Data Management, Data Science, Big Data

McLaren Applied's ATLAS software adds powerful new analytics capabilities with KX partnership

PR Newswire | August 04, 2023

Engineering and technology pioneer McLaren Applied has announced a new data and analytics partnership with leading technology company KX, maker of kdb+ the industry's most trusted Data Timehouse™ and the KDB.AI vector database. The integration will see McLaren Applied's already industry-leading ATLAS platform benefit from integration with KX's advanced kdb+ vector native, time series database, giving motorsport teams the ability to monitor race data, run complex AI and ML queries, and make real-time decisions in the garage for maximum benefit. McLaren Applied's ATLAS (Advanced Telemetry Linked Acquisition System) software package captures, distributes, displays and analyses data from control and data logging systems. Typically used in Motorsport and Automotive applications to date, the addition of KX's third-party software brings the power of ATLAS to other industries and use cases, such as Condition Monitoring, offering better prediction and detection of anomalies, and enabling operators to take preventative action before problems arise. ATLAS users can now leverage cutting-edge data analysis and visualisation enhanced by KX's extreme scalability and market-leading performance. Both powerful and efficient, with a memory footprint of only 800kb, kdb+ can process workloads up to one hundred times faster than traditional stores and at a fraction of the cost. Using this power to augment the insights provided by ATLAS, complex analyses of large datasets in real-time become simpler and easier than ever. Conversely, existing KX customers can also now leverage ATLAS's capability to better understand the behaviour of multiple systems and subsystems via forensic data examination of high frequency data. This not only offers a better way of visualising higher rate data, but allows users to manipulate and process data for more in-depth analysis. Speaking of the announcement, Richard Saxby, Director, Motorsport at McLaren Applied said: "The integration of KX's kdb+ software with our already industry-leading ATLAS platform is fantastic news for both McLaren Applied and our customers. This partnership demonstrates our continued determination to deliver ever greater power, speed and agility to race teams on the pit wall, enabling them to do the same on track. It also opens opportunities for us to bring the power of ATLAS to customers in new markets. "We look forward to seeing how kdb+ compatibility enhances our customers' capability and experience, demonstrating the full potential of ATLAS that can be realised through further in-house and third-party development." Ashok Reddy, CEO at KX, added: "KDB.AI, the industry's number one vector database, handles both structured time series and unstructured data with unparalleled proficiency - a critical function in the fast-paced world of automotive racing. With McLaren Applied, an industry pace-setter renowned for its cutting-edge technology and high-performance solutions, we can bolster the capabilities of the ATLAS platform, already one of the fastest data management and analytics platforms. We are thrilled to further fortify ATLAS's leading position in the industry, while supporting its expansion into new sectors" About McLaren Applied More than three decades in F1 and other cutting-edge global motorsport has given McLaren Applied world-leading expertise in electrification, connectivity, control and sensing. This expertise is also applied to automotive, transport and mining sectors, delivering technologies at scale with a performance advantage. Our peoples' expertise, coupled with our technology and agility, is pioneering a more sustainable, intelligent and connected future. Learn more at https://mclarenapplied.com/ About KX KX is a leading provider of vector database technology for time-series, real-time, and embedded data that provides context and insights at the speed of thought. Its mission is to accelerate the speed of data and AI-driven business innovation enabling customers to transform into real-time, intelligent enterprises. Built for the most demanding data environments, our Data Timehouse™ platform is trusted by the world's top investment banks and hedge funds, and leading companies in the life and health sciences, semiconductor, telecommunications, and manufacturing industries. At the heart of our technology is the kdb+ time series and vector database, independently benchmarked as the fastest on the market. It can process and analyze time series, historical and vector data at unmatched speed and scale, empowering developers, data scientists, and data engineers to build high-performance data-driven applications and turbo-charge their favorite analytics tools in the cloud, on-premise, or at the edge. Ultimately, our technology enables the discovery of richer, actionable insights for faster decision making which drives competitive advantage and transformative growth for our customers. KX operates from more than 15 offices across North America, Europe and Asia Pacific.

Read More

Big Data Management

Cloudera and AWS Enhance Cloud Data Management and Analytics

AWS | September 11, 2023

Cloudera and AWS have signed a strategic collaboration agreement to boost cloud-native data management and analytics. Cloudera, AWS ISV WMP Partner, will use AWS services to innovate and reduce costs with its open data lakehouse. Its Data Platform is engineered to integrate directly with AWS services, providing a cost-effective and innovative platform for customers. Cloudera and Amazon Web Services (AWS) have announced a Strategic Collaboration Agreement (SCA) aimed at bolstering cloud-native data management and analytics. Under this agreement, Cloudera will harness AWS services to provide ongoing innovation and cost reduction to customers using the Cloudera open data lakehouse on AWS for enterprise generative AI. As part of this collaboration, Cloudera, already an AWS Independent Software Vendor (ISV) Workload Migration Program (WMP) Partner, will further simplify workload migration to the cloud and the purchase of Cloudera Data Platform (CDP) on AWS, leveraging AWS Marketplace credits. Cloudera has opted to run key elements of CDP on AWS, including data management, data lakes, data warehouses, operational databases, AI and machine learning, master data management, and security components. This allows customers to transition to CDP in the cloud without the need to refactor their applications, facilitating hybrid deployments. Moreover, Cloudera has designed CDP for seamless integration with various AWS services such as Amazon S3, Amazon EKS, Amazon RDS, and Amazon EC2, delivering a tightly integrated platform that reduces costs and capitalizes on AWS innovations. Customers can access AWS native services without the burden of managing integrations themselves. "Deepening our collaboration with AWS gives customers even more reasons to choose to run the Cloudera Data Platform on AWS. With tighter hardware and AWS service integration, customers get the best possible experience with strong security and governance, along with new cost reduction options to support their most critical analytical workloads, said Paul Codding, Executive Vice President of Product Management, Cloudera. He stated that Cloudera and AWS, when combined, provide organizations with the necessary tools to construct and operate data applications in a manner that can optimally cater to the unique and evolving requirements of their business. [Source: PR Newswire] Beyond technology integration, AWS and Cloudera are set to collaborate on marketing and co-selling programs for customers. The partnership solidifies Cloudera's position as a trusted AWS partner in cloud-native data management and data analytics. "Cloudera has strengthened their collaboration with AWS for shared customers to leverage their existing investments in CDP and accelerate their modernization to the cloud, said Chris Grusz, General Manager, Technology Partnerships and Marketplace at AWS. He mentioned that Cloudera is persistently innovating on AWS throughout its data management platform to deliver authentic data analytics and insights for its customers. [Source: PR Newswire] Cloudera's open data lakehouse approach enables secure data management and portable cloud-native data analytics across various cloud environments, aligning with their mission to make data transformation feasible for the future.

Read More

Big Data Management

IBM Releases Watsonx AI with Generative AI Models for Data Governance

IBM | September 08, 2023

IBM announces plans to enhance its Watsonx AI and data platform, with a focus on scaling AI impact for enterprises. Key improvements include new generative AI models, integration of foundation models, and features like Tuning Studio and Synthetic Data Generator. IBM emphasizes trust, transparency, and governance in training and plans to incorporate AI into its hybrid cloud solutions, although implementation difficulty and cost may be issues. IBM reveals its plans to introduce new generative AI foundation models and enhancements to its Watsonx AI and data platform. The goal is to provide enterprises with the tools they need to scale and accelerate the impact of AI in their operations. These improvements include a technical preview for watsonx.governance, the addition of new generative AI data services to watsonx.data, and the integration of watsonx.ai foundation models into select software and infrastructure products. Developers will have the opportunity to explore these capabilities and models at the IBM TechXchange Conference, scheduled to take place from September 11 to 14 in Las Vegas. The upcoming AI models and features include: 1. Granite Series Models: IBM plans to launch its Granite series models, utilizing the ‘Decoder’ architecture, is essential for large language models (LLMs). These models will support various enterprise natural language processing (NLP) tasks, including summarization, content generation, and insight extraction, with planned availability in Q3 2023. 2. Third-Party Models: IBM is currently offering Meta's Llama 2-chat 70 billion parameter model and the StarCoder LLM for code generation within watsonx.ai on IBM Cloud. IBM places a strong emphasis on trust and transparency in its training process for foundation models. They follow rigorous data collection procedures and include control points to ensure responsible deployments in terms of governance, risk assessment, privacy, bias mitigation, and compliance. IBM also intends to introduce new features across the watsonx platform: For Watsonx.ai: Tuning Studio: IBM plans to release the Tuning Studio, featuring prompt tuning, allowing clients to adapt foundation models to their specific enterprise data and tasks. This is expected to be available in 3Q23. Synthetic Data Generator: IBM has launched a synthetic data generator, enabling users to create artificial tabular data sets for AI model training, reducing risk and accelerating decision-making. For Watsonx.data: Generative AI: IBM aims to incorporate generative AI capabilities into watsonx.data to help users discover, augment, visualize, and refine data for AI through a self-service, natural language interface. This feature is planned for technical preview in 4Q 2023. Vector Database Capability: IBM plans to integrate vector database capabilities into watsonx.data to support watsonx.ai retrieval and augmented generation use cases, also expected in the technical preview in 4Q 2023. For Watsonx.governance: Model Risk Governance for Generative AI: IBM is launching a tech preview for watsonx.governance, providing automated collection and documentation of foundation model details and model risk governance capabilities. Dinesh Nirmal, Senior Vice President, Products, IBM Software, stated that IBM is dedicated to supporting clients throughout the AI lifecycle, from establishing foundational data strategies to model tuning and governance. Additionally, IBM will offer AI assistants to help clients scale AI's impact across various enterprise use cases, such as application modernization, customer care, and HR and talent management. IBM also intends to integrate watsonx.ai innovations into its hybrid cloud software and infrastructure products, including intelligent IT automation and developer services. IBM's upgrades to the Watsonx AI and data platform offer promise but, come with potential drawbacks. Implementation complexity and the need for additional training may create a steep learning curve. The associated costs of advanced technology could be prohibitive for smaller organizations. The introduction of generative AI and synthetic data raises data privacy and security concerns. Additionally, despite efforts for responsible AI, the risk of bias in models necessitates ongoing vigilance to avoid legal and ethical issues.

Read More

Big Data Management, Data Science, Big Data

McLaren Applied's ATLAS software adds powerful new analytics capabilities with KX partnership

PR Newswire | August 04, 2023

Engineering and technology pioneer McLaren Applied has announced a new data and analytics partnership with leading technology company KX, maker of kdb+ the industry's most trusted Data Timehouse™ and the KDB.AI vector database. The integration will see McLaren Applied's already industry-leading ATLAS platform benefit from integration with KX's advanced kdb+ vector native, time series database, giving motorsport teams the ability to monitor race data, run complex AI and ML queries, and make real-time decisions in the garage for maximum benefit. McLaren Applied's ATLAS (Advanced Telemetry Linked Acquisition System) software package captures, distributes, displays and analyses data from control and data logging systems. Typically used in Motorsport and Automotive applications to date, the addition of KX's third-party software brings the power of ATLAS to other industries and use cases, such as Condition Monitoring, offering better prediction and detection of anomalies, and enabling operators to take preventative action before problems arise. ATLAS users can now leverage cutting-edge data analysis and visualisation enhanced by KX's extreme scalability and market-leading performance. Both powerful and efficient, with a memory footprint of only 800kb, kdb+ can process workloads up to one hundred times faster than traditional stores and at a fraction of the cost. Using this power to augment the insights provided by ATLAS, complex analyses of large datasets in real-time become simpler and easier than ever. Conversely, existing KX customers can also now leverage ATLAS's capability to better understand the behaviour of multiple systems and subsystems via forensic data examination of high frequency data. This not only offers a better way of visualising higher rate data, but allows users to manipulate and process data for more in-depth analysis. Speaking of the announcement, Richard Saxby, Director, Motorsport at McLaren Applied said: "The integration of KX's kdb+ software with our already industry-leading ATLAS platform is fantastic news for both McLaren Applied and our customers. This partnership demonstrates our continued determination to deliver ever greater power, speed and agility to race teams on the pit wall, enabling them to do the same on track. It also opens opportunities for us to bring the power of ATLAS to customers in new markets. "We look forward to seeing how kdb+ compatibility enhances our customers' capability and experience, demonstrating the full potential of ATLAS that can be realised through further in-house and third-party development." Ashok Reddy, CEO at KX, added: "KDB.AI, the industry's number one vector database, handles both structured time series and unstructured data with unparalleled proficiency - a critical function in the fast-paced world of automotive racing. With McLaren Applied, an industry pace-setter renowned for its cutting-edge technology and high-performance solutions, we can bolster the capabilities of the ATLAS platform, already one of the fastest data management and analytics platforms. We are thrilled to further fortify ATLAS's leading position in the industry, while supporting its expansion into new sectors" About McLaren Applied More than three decades in F1 and other cutting-edge global motorsport has given McLaren Applied world-leading expertise in electrification, connectivity, control and sensing. This expertise is also applied to automotive, transport and mining sectors, delivering technologies at scale with a performance advantage. Our peoples' expertise, coupled with our technology and agility, is pioneering a more sustainable, intelligent and connected future. Learn more at https://mclarenapplied.com/ About KX KX is a leading provider of vector database technology for time-series, real-time, and embedded data that provides context and insights at the speed of thought. Its mission is to accelerate the speed of data and AI-driven business innovation enabling customers to transform into real-time, intelligent enterprises. Built for the most demanding data environments, our Data Timehouse™ platform is trusted by the world's top investment banks and hedge funds, and leading companies in the life and health sciences, semiconductor, telecommunications, and manufacturing industries. At the heart of our technology is the kdb+ time series and vector database, independently benchmarked as the fastest on the market. It can process and analyze time series, historical and vector data at unmatched speed and scale, empowering developers, data scientists, and data engineers to build high-performance data-driven applications and turbo-charge their favorite analytics tools in the cloud, on-premise, or at the edge. Ultimately, our technology enables the discovery of richer, actionable insights for faster decision making which drives competitive advantage and transformative growth for our customers. KX operates from more than 15 offices across North America, Europe and Asia Pacific.

Read More

More featured news