Analytics
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Written by David Marshall Exabeam has added to their flagship behavioral analytics product, introducing an updated case management module. The addition of case management functionality into Exabeam Advanced Analytics and Exabeam Entity Analytics, its user and entity behavior analytics solutions. The updated feature will help security teams organize and streamline their response efforts to boost security operation center (SOC) productivity. Exabeam Case Management is an optional module that provides a customizable user interface designed for the workflows of security teams, and that adds intelligence to help analysts resolve incidents more efficiently. Machine learning helps make the interface context aware, presenting users with relevant fields, values, and data for different incident types. The resulting workflows bring pertinent details to analysts when and where they are needed. New features of the Exabeam Case Management module are:
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Grazed from Striim
Striim, provider of an enterprise-grade platform for streaming data integration, today announced the general availability of version 3.8.4 of the Striim platform. This new release strengthens the platform's capabilities in helping organizations with their transition to, and use of, cloud-based analytics by creating enterprise-grade, real-time data pipelines to feed different layers of their cloud environment. Available as a cloud service, Striim enables companies to reap the agility and cost-savings benefits of cloud-based analytics with real-time data movement, scalability, and faster time-to-market. With the new 3.8.4 release, the Striim platform can support organizations across all layers of their cloud-based analytical environment by bringing real-time data to:
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Grazed from Uila
Uila Inc., the Multi-Cloud Monitoring and Analytics company, today released support for seamless Multi-Cloud visibility across all Private and Public Cloud deployments including VMware, Microsoft Hyper-V, Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platforms. Uila's new Multi-Cloud version provides a single pane of glass to monitor performance, capacity and resource allotments simultaneously across Multiple Cloud technologies, both public and private. With this new release, IT Operations and Cloud IT teams are now armed with critical information that will help them proactively plan application deployment, monitor performance, prevent and solve service degradation issues for workloads that span multiple clouds. Since the first release, Uila's Application Dependency Map has provided detailed, dynamic Application topology maps for multi-tier applications, allowing proactive troubleshooting of issues at lightning speeds with full visibility into the behavior, health and dependencies across applications and infrastructure. With the new release, this capability has been further expanded with full workload dependency visibility across multiple clouds and cloud providers. IT teams can now pinpoint performance bottlenecks for workloads spanning multiple clouds in a single view. This dynamic Multi-Cloud Dependency Mapping & performance analysis capability is not only important for solving application performance issues, but provides the needed visibility for organizations who may be switching cloud providers or rolling back to an on-premise datacenter.
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Grazed from Zenoss
Vendors across many segments have long endeavored to help prevent IT service outages and improve overall IT performance. These vendors have taken different approaches, including infrastructure monitoring, artificial intelligence operations (AIOps), log analytics, and more. Some approaches collect performance data from systems directly, some rely on events, some rely on logs, while others rely on data sent from agents. Zenoss Cloud represents the first platform that encompasses all of these approaches. Key to successfully achieving this strategy was developing the unique ability to collect and analyze all types of structured and unstructured data in the same context - widely considered the holy grail of IT operations management. Zenoss Cloud introduces the first operations data plane that streams and normalizes all machine data, uniquely enabling this emergence of context for preventing IT service disruptions in complex, modern environments.
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Grazed from Hortonworks and Google Cloud
![]() HDP now integrates with Google Cloud Storage, which offers consistent cloud storage for running big data workloads. With HDP on GCP, customers get:
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Grazed from Amazon
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Grazed from SWIM.AI
SWIM.AI, the edge intelligence software company, today exited stealth and announced the general availability of its edge software solution, SWIM EDX, delivering edge intelligence and real-time business and operational insights. Current business intelligence solutions require large volumes of time-series data to be reduced, streamed to the cloud, stored, cleaned, analyzed and then modelled - at great expense and often with significant delays. By applying analytics, self-training digital twins and edge computing, SWIM EDX allows manufacturers, infrastructure providers, enterprises, cities and IoT vendors to analyze and take immediate action on fast edge data. In addition, the company today announced key additions to its management team, including Simon Crosby as chief technology officer, Simon Aspinall as chief sales and marketing officer, and Ramana Jonnala as chief product officer. "Edge devices and data volumes are growing exponentially, leaving enterprises swamped," said Holger Mueller, VP and principal analyst for Constellation Research. "That data, however, holds insights that can truly transform production, efficiency and a multitude of other factors. Being able to analyze that data, and therefore predict system performance on the fly puts enterprises ahead of the game."
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Grazed from Databricks
![]() Designed by Databricks in collaboration with Microsoft, Azure Databricks combines the best of Databricks' Spark-based cloud service and Azure to help customers accelerate innovation with one-click set up, streamlined workflows and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts. The integrated service provides Databricks' Unified Analytics Platform integrated with the Azure cloud platform, encompassing the Azure Portal; Azure Active Directory; and other data services on Azure, including Azure SQL Data Warehouse, Azure Cosmos DB, Azure Data Lake Store; and Microsoft Power BI.
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Grazed from Inpixon
![]() “After extensive research and several successful test scenarios, we are very confident that AWS is the right choice for Inpixon’s IPA,” said Shirish Tangirala, Inpixon CPO. “IPA’s analytics engine requires a robust, high-performance infrastructure to compute an immense amount of locational data captured hourly by our sensors in order to deliver positional accuracy and intelligence. Based on performance, scalability, and security, AWS is the ideal fit.”
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