Remove Analysis Remove Analytics Remove IoT Remove Lambda
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Using Real-Time Digital Twins for Aggregate Analytics

ScaleOut Software

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.

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Using Real-Time Digital Twins for Aggregate Analytics

ScaleOut Software

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.

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Unlocking the Value of Device Data with AWS Greengrass.

All Things Distributed

Local aggregation and filtering of data allows customers to send only high-value data to the cloud for storage and analysis. AWS Greengrass provides the following features: Local execution ofAWS Lambda functions written in Python 2.7 AWS Greengrass uses the same certificate-based mutual authentication that AWS IoT uses.

AWS 118
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Expanding the AWS Cloud: Introducing the AWS Europe (London) Region

All Things Distributed

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
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Expanding the Cloud: Introducing Amazon QuickSight

All Things Distributed

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
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A one size fits all database doesn't fit anyone

All Things Distributed

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