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

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

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

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. Root-cause analysis. Insight into business KPIs.

Artificial Intelligence 232

Artificial Intelligence Monitoring Infrastructure Cloud 232

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

Dynatrace

OCTOBER 1, 2021

As more organizations adopt cloud-native architectures, they are also looking for ways to implement AIOps, harnessing AI as a way to automate more processes throughout the DevSecOps life cycle. An advanced observability solution can also be used to automate more processes, increasing efficiency and innovation among Ops and Apps teams.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Others include fleet and traffic management, healthcare, financial services, IoT, and e-commerce recommendations.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Others include fleet and traffic management, healthcare, financial services, IoT, and e-commerce recommendations.

Code 52

Code Analytics Healthcare IoT 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. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

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. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

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

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Others include fleet and traffic management, healthcare, financial services, IoT, and e-commerce recommendations.

Code 52

Code Analytics Healthcare IoT 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. What Are Real-Time Digital Twins?

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. What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 52

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

All Things Distributed

JUNE 7, 2017

This is because data gets more valuable when it can be processed together with other data. At the same time, it can be valuable to process some data right at the source where it is generated. When you can't address scenarios such as these, the value of data you don't process is lost. Law of the Land.

AWS 118

AWS IoT Lambda Storage 118

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications such as these require. It’s not enough to just pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.

Logistics 52

Logistics Retail Analytics Azure 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. Architectural research in these areas remains traditionally focused on the analysis of object detection and recognition algorithms (e.g. Yolo , ResNet50 ).

Wireless 54

Wireless IoT Analytics Architecture 54

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. User experience and business analytics. What does APM stand for?

Monitoring 149

Monitoring Mobile Social Media Artificial Intelligence 149

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

Dynatrace

JUNE 13, 2019

Data analysis within large and highly dynamic microservices environments is the biggest challenge that Application Performance Monitoring (APM) vendors face today. The real challenge is robust and effective analysis of such data. Why are we doing this? What Dynatrace will contribute.

IoT 46

IoT C++ Analytics Java 46

All Things Distributed

DECEMBER 13, 2016

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. Take GoSquared , a UK startup that runs all its development and production processes on AWS, as an example.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

OCTOBER 7, 2015

In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data. However, the data infrastructure to collect, store and process data is geared toward developers (e.g., Big data challenges.

Cloud 137

Cloud Big Data AWS Analytics 137

All Things Distributed

JUNE 21, 2018

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. The data warehouse also persists the processed data directly into Aurora MySQL and Amazon Redshift to support both operational and analytical queries.

Database 167

Database AWS Games Latency 167

All Things Distributed

NOVEMBER 15, 2016

Previously, I wrote about Amazon QuickSight , a new service targeted at business users that aims to simplify the process of deriving insights from a wide variety of data sources quickly, easily, and at a low cost. QuickSight is a very fast, cloud-powered, business intelligence service for the 1/10th the cost of old-guard BI solutions.

Analytics 152

Analytics Availability Media Social Media 152