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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 111
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Achieving Trusted AI in Manufacturing

Cloudera

Here are some of the key use cases: Predictive maintenance: With time series data (sensor data) coming from the equipment, historical maintenance logs, and other contextual data, you can predict how the equipment will behave and when the equipment or a component will fail. Eliminate data silos. That is a very low number.

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Deep dive into the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

In this post, we dive deep into the tool, walking through all steps from log ingestion, transformation, visualization, and architecture design to calculate TCO. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget.

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How Cargotec uses metadata replication to enable cross-account data sharing

AWS Big Data

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization.

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Three Trends for Modernizing Analytics and Data Warehousing in 2019

Cloudera

The most common big data use case is data warehouse optimization. Big data architecture is used to augment different applications, operating alongside or in a discrete fashion with a data warehouse. A big data implementation may even replace a data warehouse entirely with a data lake.

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Modern Data Architecture for Telecommunications

Cloudera

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Previously, there were three types of data structures in telco: .

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The Cloud Connection: How Governance Supports Security

Alation

A useful feature for exposing patterns in the data. Visual Profiling. Supports the ability to interact with the actual data and perform analysis on it. Pushing data to a data lake and assuming it is ready for use is shortsighted. Parametrization. A technique to automate changes in iterative passes.