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Harnessing Streaming Data: Insights at the Speed of Life

Sisense

The world is moving faster than ever, and companies processing large amounts of rapidly changing or growing data need to evolve to keep up — especially with the growth of Internet of Things (IoT) devices all around us. Let’s look at a few ways that different industries take advantage of streaming data.

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Improve power utility operational efficiency using smart sensor data and Amazon QuickSight

AWS Big Data

Data collection and processing are handled by a third-party smart sensor manufacturer application residing in Amazon Virtual Private Cloud (Amazon VPC) private subnets behind a Network Load Balancer. The AWS Glue Data Catalog contains the table definitions for the smart sensor data sources stored in the S3 buckets.

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

AWS Big Data

Based on the statistics of individual and aggregated application runs per queue and per user, you can determine the existing workload distribution by user. He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services. Jiseong Kim is a Senior Data Architect at AWS ProServe.

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Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

However, you might face significant challenges when planning for a large-scale data warehouse migration. Data engineers are crucial for schema conversion and data transformation, and DBAs can handle cluster configuration and workload monitoring. This can help identify any discrepancies in data values or data types.

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Introducing the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

YARN log collector The HMDK TCO tool enables a simple way to capture Hadoop YARN logs, which include the Hadoop job runs statistics and the corresponding resource usages. He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services. Jiseong Kim is a Senior Data Architect at AWS ProServe.

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What is a Data Pipeline?

Jet Global

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.