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Exploring real-time streaming for generative AI Applications

AWS Big Data

Streaming data facilitates the constant flow of diverse and up-to-date information, enhancing the models’ ability to adapt and generate more accurate, contextually relevant outputs. Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor.

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#ClouderaLife Employee Spotlight: Sherry Zhou, Engineering Manager

Cloudera

Her team’s objectives are to, first, make it easier for analysts to explore data, enabling them to uncover interesting trends in product features and performance. A second objective is to make it easier for less technical users to interpret data through the creation of dashboards.

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Ingest, transform, and deliver events published by Amazon Security Lake to Amazon OpenSearch Service

AWS Big Data

With OCSF support, the service can normalize and combine security data from AWS and a broad range of enterprise security data sources. OpenSearch Service is a fully managed and scalable log analytics framework that is used by customers to ingest, store, and visualize data. For this post, we select All log and event sources.

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Operational Finance in the Age of Covid-19: Time to Change the Basics?

Jet Global

Not only have finance teams had to close companies’ books remotely, but they’ve also been required to provide the insight and information needed for some extremely complex decision-making, and continuously plan and forecast for events with little or no historical context. Tip 3: Make decisions with operational data.

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Building a culture of data-driven decisions and insights with IBM Business Analytics

IBM Big Data Hub

Most recently we held an event at the IBM Data and AI Forum in Germany ( available on demand here ) where we shared the latest news in our business analytics portfolio. The post Building a culture of data-driven decisions and insights with IBM Business Analytics appeared first on Journey to AI Blog. We are here to help!

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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

The data lake implemented by Ruparupa uses Amazon S3 as the storage platform, AWS Database Migration Service (AWS DMS) as the ingestion tool, AWS Glue as the ETL (extract, transform, and load) tool, and QuickSight for analytic dashboards. The audience of these few reports was limited—a maximum of 20 people from management.

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12 considerations when choosing MES software

IBM Big Data Hub

They can create and distribute information across the production line, dispatching work orders and work instructions based on trigger events. User-friendliness: The software should be easy to use, with intuitive dashboards and user interfaces.