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The Superpowers of Ontotext’s Relation and Event Detector

Ontotext

From a technological perspective, RED combines a sophisticated knowledge graph with large language models (LLM) for improved natural language processing (NLP), data integration, search and information discovery, built on top of the metaphactory platform. It compares actual price changes to expected changes based on historical data.

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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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The Data Journey: From Raw Data to Insights

Sisense

In all cases the data will eventually be loaded into a different place, so it can be managed, and organized, using a package such as Sisense for Cloud Data Teams. Using data pipelines and data integration between data storage tools, engineers perform ETL (Extract, transform and load).

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AML: Past, Present and Future – Part III

Cloudera

It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data. It also supports a number of frameworks that can process data in parallel, in batch or in streams, in a variety of languages. Entity Resolution and Data Enrichment. Cloudera Enterprise.

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What is a Data Pipeline?

Jet Global

Data pipelines play a critical role in modern data-driven organizations by enabling the seamless flow and transformation of substantial amounts of data across various systems and apps. The pipeline starts by extracting data from one or more sources, such as databases, files, APIs, or other data repositories.