ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

All Things Distributed

MARCH 11, 2015

Many of these innovations will have a significant analytics component or may even be completely driven by it. For example many of the Internet of Things innovations that we have seen come to life in the past years on AWS all have a significant analytics components to it. Cloud analytics are everywhere.

Analytics 135

Analytics Cloud Healthcare Retail 135

Dynatrace

APRIL 5, 2021

Similar to AWS Lambda , Azure Functions is a serverless compute service by Microsoft that can run code in response to predetermined events or conditions (triggers), such as an order arriving on an IoT system, or a specific queue receiving a new message. It automatically manages all the computing resources those processes require.

Azure 136

Azure Serverless IoT Lambda 136

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. We are increasingly surrounded by intelligent IoT devices, which have become an essential part of our lives and an integral component of business and industrial infrastructures. The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

ScaleOut Software

AUGUST 18, 2018

In previous blogs , we have explored the power of the digital twin model for stateful stream-processing. Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g.,

IoT 45

IoT Ecommerce Analytics Latency 45

Dynatrace

SEPTEMBER 30, 2021

AWS Certified Data Analytics – Specialty: Highly knowledgeable data analytics pros who have already worked with AWS for some time should consider getting this certification. Data analytics. If your company is pursuing AWS certification for a team, AWS Certification Exam Vouchers make the process easier. Machine learning.

AWS 205

AWS Best Practices Analytics Cloud 205

ScaleOut Software

AUGUST 18, 2018

In previous blogs , we have explored the power of the digital twin model for stateful stream-processing. Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g.,

IoT 40

IoT Ecommerce Analytics Latency 40

ScaleOut Software

APRIL 6, 2021

With the ScaleOut Digital Twin Streaming Service , an Azure-hosted cloud service, ScaleOut Software introduced breakthrough capabilities for streaming analytics using the real-time digital twin concept. This simplifies the installation process and ensures portability across operating systems.

IoT 52

IoT Azure Analytics Healthcare 52

Dynatrace

NOVEMBER 8, 2021

These solutions provide performance metrics for applications, with specific insights into the statistics, such as the number of transactions processed by the application or the response time to process such transactions. APM products form a baseline for these metrics and monitor the applications for any variance from the baseline.”

Artificial Intelligence 229

Artificial Intelligence Monitoring Infrastructure Cloud 229

ScaleOut Software

MAY 4, 2018

Traditional stream-processing and complex event processing systems, such as Apache Storm and Software AG’s Apama , have focused on extracting interesting patterns from incoming data with stateless applications. Michigan) in 2002 for use in product life cycle management, it was recently popularized for IoT by Gartner in a 2017 report.

Processing 40

Processing IoT Programming Software Engineering 40

ScaleOut Software

MAY 4, 2018

Traditional stream-processing and complex event processing systems, such as Apache Storm and Software AG’s Apama , have focused on extracting interesting patterns from incoming data with stateless applications. Michigan) in 2002 for use in product life cycle management, it was recently popularized for IoT by Gartner in a 2017 report.

Processing 40

Processing IoT Programming Software Engineering 40

VoltDB

JUNE 9, 2017

Historically, telco analytics have been limited and difficult. Analytics and insights have always taken a back seat to the first two priorities – accurate data processing and billing. Information needs to be handled in real-time, not via batch processing. Does this affect our analytics strategy?

Analytics 40

Analytics Strategy Network Games 40

VoltDB

JUNE 9, 2017

Historically, telco analytics have been limited and difficult. Analytics and insights have always taken a back seat to the first two priorities – accurate data processing and billing. Information needs to be handled in real-time, not via batch processing. Does this affect our analytics strategy?

Analytics 40

Analytics Strategy Network Games 40

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. For example, heart-rate telemetry from a smart watch cannot be effectively evaluated in isolation. Sign up to use the service here.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. For example, heart-rate telemetry from a smart watch cannot be effectively evaluated in isolation. Sign up to use the service here.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

SEPTEMBER 20, 2018

These are exciting times in the evolution of stream-processing. As we have seen in previous blogs , the digital twin model offers a breakthrough approach to structuring stateful stream-processing applications. It represents a big step forward for building stream-processing applications.

Programming 63

Programming IoT Java Analytics 63

Dynatrace

JULY 6, 2020

Let’s look at the Azure DB for MariaDB overview as an example. Azure HDInsight is a fully-managed cloud service on Azure that makes it easy to process massive amounts of data in hyper-scale environments. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 146

Azure Cloud Big Data Virtualization 146

ScaleOut Software

AUGUST 20, 2020

Simplifying the Development Process with Mock Environments. This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. The method contains domain-specific knowledge, such as a predictive analytics algorithm for truck engines.

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

Simplifying the Development Process with Mock Environments. This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. The method contains domain-specific knowledge, such as a predictive analytics algorithm for truck engines.

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

DECEMBER 10, 2019

For example, consider a large power grid with tens or hundreds of thousands of nodes, such as power poles, controllers, and other critical elements. Importantly, it also can record the results of its analysis in its data object and subject these results to real-time, aggregate analytics. We invite you to check it out.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

For example, consider a large power grid with tens or hundreds of thousands of nodes, such as power poles, controllers, and other critical elements. Importantly, it also can record the results of its analysis in its data object and subject these results to real-time, aggregate analytics. We invite you to check it out.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

For example, consider a large power grid with tens or hundreds of thousands of nodes, such as power poles, controllers, and other critical elements. Importantly, it also can record the results of its analysis in its data object and subject these results to real-time, aggregate analytics. We invite you to check it out.

Code 52

Code Analytics Healthcare IoT 52

Dynatrace

JUNE 1, 2021

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications — including a company’s customers and employees. Mobile apps, websites, and business applications are typical use cases for monitoring.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

All Things Distributed

MAY 3, 2017

Most of Germany's hidden champions have earned their reputation through hard work: they have been optimizing their processes over decades. They have invested the time to perfect their processes and develop high-quality products for their customers. The power of persistence versus the speed of adjustment. Probably not.

Logistics 72

Logistics IoT Analytics Innovation 72

ScaleOut Software

SEPTEMBER 20, 2018

These are exciting times in the evolution of stream-processing. As we have seen in previous blogs , the digital twin model offers a breakthrough approach to structuring stateful stream-processing applications. It represents a big step forward for building stream-processing applications.

Programming 40

Programming IoT Java Analytics 40

ScaleOut Software

JUNE 22, 2020

Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT. The following diagram shows the evolution of in-memory computing from distributed caching to stream-processing with real-time digital twins.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 22, 2020

Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT. The following diagram shows the evolution of in-memory computing from distributed caching to stream-processing with real-time digital twins.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. Orchestrate the processing flow across an end-to-end infrastructure. Advantages can be harnessed in terms of execution efficiency as well as realizing immersive VR usages for example. Generate interactive and immersive content.

Wireless 54

Wireless IoT Analytics Architecture 54

Adrian Cockcroft

FEBRUARY 13, 2023

This is the AWS Professional Services built tooling that customers can use to track the carbon footprint of their operations and processes, along with a customer example. Good example, well presented interesting new material. AWS Inferentia 2.6x shorter training time, saving 54% energy and 75% cost.

AWS 64

AWS Energy Architecture Programming 64

Dynatrace

JUNE 13, 2019

The Dynatrace platform automatically integrates OpenTelemetry data, thereby providing the highest possible scalability, enterprise manageability, seamless processing of data, and, most importantly the best analytics through Davis (our AI-driven analytics engine), and automation support available. What Dynatrace will contribute.

IoT 45

IoT C++ Analytics Java 45

All Things Distributed

DECEMBER 13, 2016

Take Peterborough City Council as an example. The council has deployed IoT Weather Stations in Schools across the City and is using the sensor information collated in a Data Lake to gain insights on whether the weather or pollution plays a part in learning outcomes. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

OCTOBER 7, 2015

However, the data infrastructure to collect, store and process data is geared toward developers (e.g., However, the process of deriving actionable insights out of this wide variety of data sources is not easy. QuickSight is a fast, cloud native, scalable, business intelligence service for the 1/10th the cost of old-guard BI solutions.

Cloud 137

Cloud Big Data AWS Analytics 137

All Things Distributed

JUNE 21, 2018

Airbnb is a great example of a customer building high-performance and scalable applications with Amazon Aurora. Use cases such as gaming, ad tech, and IoT lend themselves particularly well to the key-value data model where the access patterns require low-latency Gets/Puts for known key values. Take Expedia, for example.

Database 167

Database AWS Games Latency 167

All Things Distributed

MAY 21, 2018

We already have an idea of how digitalization, and above all new technologies like machine learning, big-data analytics or IoT, will change companies' business models — and are already changing them on a wide scale. Only parts of the processes are being performed by machines, or at least supported by them.

Artificial Intelligence 76

Artificial Intelligence Technology Technology IoT 76

Abhishek Tiwari

NOVEMBER 3, 2018

Most of the CMS vendors dodge questions of evolution by talking about incremental innovation primarily focused on customer experience (CX) such as analytics and personalisation. This made whole publishing process really slow and painful and CMS was part of growing pain. Decoupled CMS vs. headless CMS.

Systems 63

Systems Cache Website Network 63