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What is SAS Event Stream Processing?

Understanding the importance of streaming data generated from various operations, transactions, sensors, and IoT devices is crucial for maximizing its potential. SAS's event stream processing provides a robust solution that integrates streaming data quality, advanced analytics, and a wide array of both SAS and open source machine learning methods, all complemented by high-frequency analytics capabilities. This cohesive approach allows for the effective connection, interpretation, cleansing, and analysis of streaming data without disruption. No matter the speed at which your data is produced, the sheer amount of data you handle, or the variety of sources you draw from, you can manage everything with ease through an intuitive interface. In addition, by establishing patterns and preparing for diverse scenarios across your organization, you can maintain flexibility and address challenges proactively as they arise, ultimately boosting your overall operational efficiency while fostering a culture of continuous improvement. This adaptability is essential in today's fast-paced data-driven environment.

What is Azure Data Explorer?

Azure Data Explorer offers a swift and comprehensive data analytics solution designed for real-time analysis of vast data streams originating from various sources such as websites, applications, and IoT devices. You can pose questions and conduct iterative data analyses on the fly, enhancing products and customer experiences, overseeing device performance, optimizing operations, and ultimately boosting profitability. This platform enables you to swiftly detect patterns, anomalies, and trends within your data. Discovering answers to your inquiries becomes a seamless process as you delve into new subjects. With a cost-effective structure, you can execute an unlimited number of queries without hesitation. Efficiently uncover new opportunities within your data, all while utilizing a fully managed and user-friendly analytics service that allows you to concentrate on deriving insights rather than managing infrastructure. The ability to quickly adapt to dynamic and rapidly changing data environments is a key feature of Azure Data Explorer, making it a vital tool for simplifying analytics across all forms of streaming data. This capability not only enhances decision-making but also empowers organizations to stay ahead in an increasingly data-driven landscape.

Media

Media

Integrations Supported

Azure Marketplace
Azure Monitor
Azure Time Series Insights
Blink
Microsoft Azure

Integrations Supported

Azure Marketplace
Azure Monitor
Azure Time Series Insights
Blink
Microsoft Azure

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$0.11 per hour
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

SAS Institute

Date Founded

1976

Company Location

United States

Company Website

www.sas.com/en_us/software/event-stream-processing.html

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/products/data-explorer/

Categories and Features

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

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