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Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore federation

AWS Big Data

For detailed information on managing your Apache Hive metastore using Lake Formation permissions, refer to Query your Apache Hive metastore with AWS Lake Formation permissions. In this post, we present a methodology for deploying a data mesh consisting of multiple Hive data warehouses across EMR clusters.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging. Example Corp.

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Large Language Models and Data Management

Ontotext

I did some research because I wanted to create a basic framework on the intersection between large language models (LLM) and data management. But there are also a host of other issues (and cautions) to take into consideration. It was emphasized many times that LLMs are only as good as the data sources.

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The Data-Centric Revolution: Report From the Front Lines

TDAN

Earlier this month we hosted the second annual Data-Centric Architecture Forum (#DCAF2020) in Fort Collins, CO. Last year, (2019) we hosted the first Data-Centric Architecture conference. In 2019, the focus was on getting a sketch of a reference architecture (click here to see). Trip report).

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Understanding Digital Interactions in Real-Time

CIO Business Intelligence

But this glittering prize might cause some organizations to overlook something significantly more important: constructing the kind of event-driven data architecture that supports robust real-time analytics. We can, in the semantics of the software world, refer to digitally mediated business activities asreal-time events.

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Big Data Ingestion: Parameters, Challenges, and Best Practices

datapine

Operations data: Data generated from a set of operations such as orders, online transactions, competitor analytics, sales data, point of sales data, pricing data, etc. The gigantic evolution of structured, unstructured, and semi-structured data is referred to as Big data. Videos, pictures etc.

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Delivering Power Platform Projects: Truths from the Field

Jen Stirrup

Just because technology is easy to use, it does not follow that the data is easy to understand. Don’t be fooled by easy-to-use technology; data can still be hard. Logic Apps are hosted in Azure and have a code view rather than a ‘business user coder’ view. Compliant or Complaint?