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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

5) How Do You Measure Data Quality? In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. These processes could include reports, campaigns, or financial documentation.

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Amazon OpenSearch Service search enhancements: 2023 roundup

AWS Big Data

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. Lexical search In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word.

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Enhancing Knowledge Discovery: Implementing Retrieval Augmented Generation with Ontotext Technologies

Ontotext

So we can easily integrate the information from both textual documents and structured RDF entities into an LLM-driven application. The examples below use OpenAI’s ChatGPT, but they can be applied against other LLM chatbots, including self-hosted ones. Talk to Your Graph GraphDB 10.4

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Achieve high availability in Amazon OpenSearch Multi-AZ with Standby enabled domains: A deep dive into failovers

AWS Big Data

During the query phase of a search request, the coordinator determines the shards to be queried and sends a request to the data node hosting the shard copy. The query is run locally on each shard and matched documents are returned to the coordinator node.

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Octopai Users Do More with Enhanced Data Lineage Capabilities + Complete BI Data Catalog

Octopai

Manually add objects and or links to represent metadata that wasn’t included in the extraction and document descriptions for user visualization. Download upper and column-to-column lineage to Excel/CSV in order to document, verify development and change requests. We call this feature: Expand. Column-to-column lineage.

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Build and share a business capability model with Amazon QuickSight

AWS Big Data

The only document given to Bob was PowerPoint slides and the names of the head of each department to get more information. To collect that information, Bob gets in touch with the head of each department, who in turn refer him to their development leads, who in turn give him a bunch of technical documents that explain how APIs are being used.

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Introducing the vector engine for Amazon OpenSearch Serverless, now in preview

AWS Big Data

This enables you to process a user’s query to find the closest vectors and combine them with additional metadata without relying on external data sources or additional application code to integrate the results. The vector engine’s compute capacity used for data ingestion, and search and query are measured in OpenSearch Compute Units (OCUs).