Remove Business Objectives Remove Internet of Things Remove Optimization Remove Reference
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My top learning and pondering moments at Splunk.conf22

Rocket-Powered Data Science

Observability is a business strategy: what you monitor, why you monitor it, what you intend to learn from it, how it will be used, and how it will contribute to business objectives and mission success. Reference ) Splunk Enterprise 9.0 Reference ) Splunk Enterprise 9.0 And the goodness doesn’t stop there.”

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My top learning moments at Splunk.conf23

Rocket-Powered Data Science

Such prescriptive capabilities can be more proactive, automated, and optimized, making digital resilience an objective fact for businesses, not just a business objective. By that, he was referring to being a winner with Splunk SOAR : Security Orchestration, Automation and Response.

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12 considerations when choosing MES software

IBM Big Data Hub

Gathering data from machines, sensors, operators and other Industrial Internet of Things (IIoT) devices, they provide accurate and up-to-date insights into the status of production activities. MES systems can assist managers with process management and process control, helping to facilitate optimal performance of manufacturing.

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How SOCAR handles large IoT data with Amazon MSK and Amazon ElastiCache for Redis

AWS Big Data

In this post, we provide a detailed overview of streaming messages with Amazon Managed Streaming for Apache Kafka (Amazon MSK) and Amazon ElastiCache for Redis , covering technical aspects and design considerations that are essential for achieving optimal results. We also discuss the key features, considerations, and design of the solution.

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Migrate and modernize IBM Maximo with AWS and Red Hat

IBM Big Data Hub

It is an enterprise cloud-based asset management platform that leverages artificial intelligence (AI) , the Internet of Things (IoT) and analytics to help optimize equipment performance, extend asset lifecycles and reduce operational downtime and costs.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

They should also provide optimal performance with low or no tuning. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes. Data repositories represent the hub.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

Both of these concepts resonated with our team and our objectives, and so we found ourselves supporting both to some extent. The new architecture requires that data be structured in a dimensional model to optimize for BI capabilities, but it also allows for ad hoc analytics with the flexibility to query clean and raw data.