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

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 26, 2022

DEM provides an outside-in approach to user monitoring that measures user experience (UX) in real time to ensure applications and services are available, functional, and well-performing across all channels of the digital experience, including web, mobile, and IoT.

Monitoring 196

Monitoring Social Media IoT Metrics 196

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

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., The digital twin model is worth a close look when designing the next generation of IoT applications.

IoT 45

IoT Ecommerce Analytics Latency 45

ScaleOut Software

AUGUST 18, 2018

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., The digital twin model is worth a close look when designing the next generation of IoT applications.

IoT 40

IoT Ecommerce Analytics Latency 40

Dynatrace

NOVEMBER 8, 2021

Root-cause analysis. A truly modern APM solution provides business analytics, such as conversions, release success, and user outcomes across web, mobile, and IoT channels, linking application performance to business KPIs. Insight into business KPIs.

Artificial Intelligence 226

Artificial Intelligence Monitoring Infrastructure Cloud 226

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

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

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

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. Does this affect our analytics strategy? There is no substitute for real-time analytics and action. The answer: Absolutely!

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. Does this affect our analytics strategy? There is no substitute for real-time analytics and action. The answer: Absolutely!

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. 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

Dynatrace

OCTOBER 1, 2021

Business analytics : Organizations can combine business context with full stack application analytics and performance to understand real-time business impact, improve conversion optimization, ensure that software releases meet expected business goals, and confirm that the organization is adhering to internal and external SLAs.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

ScaleOut Software

SEPTEMBER 20, 2018

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.

Programming 63

Programming IoT Java Analytics 63

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. To foster research in these categories, we provide an overview of each of these categories to understand the implications on workload analysis and HW/SW architecture research. interactive AR/VR, gaming and critical decision making).

Wireless 54

Wireless IoT Analytics Architecture 54

All Things Distributed

JUNE 7, 2017

Local aggregation and filtering of data allows customers to send only high-value data to the cloud for storage and analysis. Local messaging between functions and peripherals on the device that hosts AWS Greengrass core, and also between the core and other local devices that use the AWS IoT Device SDK. Law of the Land.

AWS 118

AWS IoT Lambda Storage 118

ScaleOut Software

AUGUST 20, 2020

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. Their analysis determines whether immediate action needs to be taken to resolve an issue (or identify an opportunity). What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

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. Their analysis determines whether immediate action needs to be taken to resolve an issue (or identify an opportunity). What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 52

Dynatrace

JUNE 1, 2021

Root-cause and impact analysis of application performance problems and business outcomes for faster, more reliable incident resolution. Business KPIs and user journey analysis (for example, login to check out) to optimize user experiences and provide transparency into how changes impact KPIs. User experience and business analytics.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

ScaleOut Software

SEPTEMBER 20, 2018

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.

Programming 40

Programming IoT Java Analytics 40

ScaleOut Software

MAY 4, 2018

For example, if an IoT application is attempting to detect whether data from a temperature sensor is predicting the failure of the medical freezer to which it is attached, it looks at patterns in the temperature changes, such as sudden spikes or a continuously upward trend, without regard to the freezer’s usage or service history.

Processing 40

Processing IoT Programming Software Engineering 40

ScaleOut Software

MAY 4, 2018

For example, if an IoT application is attempting to detect whether data from a temperature sensor is predicting the failure of the medical freezer to which it is attached, it looks at patterns in the temperature changes, such as sudden spikes or a continuously upward trend, without regard to the freezer’s usage or service history.

Processing 40

Processing IoT Programming Software Engineering 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 45

IoT C++ Analytics Java 45

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. The British Government is also helping to drive innovation and has embraced a cloud-first policy for technology adoption.

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. When you point QuickSight to a data source, data is automatically ingested into SPICE for optimal analytical query performance.

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

To scale to a larger number of users and support the growth in data volume spurred by social media, web, mobile, IoT, ad-tech, and ecommerce workloads, these tools require customers to invest in even more infrastructure to maintain performance. Enter Amazon QuickSight. While QuickSight supports multiple graph types (e.g.,

Analytics 152

Analytics Availability Media Social Media 152