Empower Your Existing Team to Attain Enterprise-Level Security
Introducing a comprehensive solution that combines SIEM, endpoint visibility, continuous monitoring, and automated responses to simplify processes, enhance visibility, and accelerate response times.
We manage the burdens of security, allowing you to reclaim valuable time in your schedule. With ready-to-use detections, filtered alerts, and established response playbooks, IT departments can derive substantial security benefits through Blumira.
Fast Setup, Instant Benefits: Seamlessly integrates with your technology ecosystem and is fully operational within hours, eliminating any waiting period.
Unlimited Data Ingestion: Enjoy predictable pricing alongside limitless data logging for comprehensive lifecycle detection.
Streamlined Compliance: Comes with one year of data retention, ready-made reports, and round-the-clock automated monitoring.
Exceptional Support with a 99.7% Customer Satisfaction Rate: Benefit from dedicated Solution Architects for product assistance, a proactive Incident Detection and Response Team developing new detections, and continuous SecOps support around the clock. With this robust offering, your team can focus on strategic initiatives while we handle the intricacies of security management.
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Teradata VantageCloud: Open, Scalable Cloud Analytics for AI
VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.
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Data Lakes on AWS
Numerous customers of Amazon Web Services (AWS) seek a data storage and analytics solution that surpasses the agility and flexibility of conventional data management systems. A data lake has emerged as an innovative and increasingly favored method for storing and analyzing data, as it enables organizations to handle various data types from diverse sources, all within a unified repository that accommodates both structured and unstructured data. The AWS Cloud supplies essential components necessary for customers to create a secure, adaptable, and economical data lake. These components comprise AWS managed services designed to assist in the ingestion, storage, discovery, processing, and analysis of both structured and unstructured data. To aid our customers in constructing their data lakes, AWS provides a comprehensive data lake solution, which serves as an automated reference implementation that establishes a highly available and cost-efficient data lake architecture on the AWS Cloud, complete with an intuitive console for searching and requesting datasets. Furthermore, this solution not only enhances data accessibility but also streamlines the overall data management process for organizations.
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Cribl Stream
Cribl Stream allows you create an observability pipeline that helps you parse and restructure data in flight before you pay to analyze it. You can get the right data in the format you need, at the right place and in the format you want. Translate and format data into any tooling scheme you need to route data to the right tool for the job or all of the job tools. Different departments can choose different analytics environments without the need to deploy new forwarders or agents. Log and metric data can go unused up to 50%. This includes duplicate data, null fields, and fields with zero analytical value. Cribl Stream allows you to trim waste data streams and only analyze what you need. Cribl Stream is the best way for multiple data formats to be integrated into trusted tools that you use for IT and Security. Cribl Stream universal receiver can be used to collect data from any machine source - and to schedule batch collection from REST APIs (Kinesis Firehose), Raw HTTP and Microsoft Office 365 APIs.
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