Remove Data Transformation Remove IT Remove Metadata
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Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

Writing SQL queries requires not just remembering the SQL syntax rules, but also knowledge of the tables metadata, which is data about table schemas, relationships among the tables, and possible column values. We discuss the challenges in maintaining the metadata as well as ways to overcome those challenges and enrich the metadata.

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Bridging the gap between mainframe data and hybrid cloud environments

CIO Business Intelligence

A high hurdle many enterprises have yet to overcome is accessing mainframe data via the cloud. Mainframes hold an enormous amount of critical and sensitive business data including transactional information, healthcare records, customer data, and inventory metrics.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. Recently, EUROGATE has developed a digital twin for its container terminal Hamburg (CTH), generating millions of data points every second from Internet of Things (IoT)devices attached to its container handling equipment (CHE).

IoT 107
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How to Implement Data Lineage Mapping Techniques

Octopai

Ever reflect on what it would be like to be a piece of data that enters your BI system? It ain’t easy being data. Then again, it ain’t easy to be a BI developer trying to track data through a stream of twists, turns, transformations, and multiple BI systems. Look for the Metadata. Honey, I’m home!

Metadata 133
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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

What Is Data Quality Management (DQM)? Data quality management is a set of practices that aim at maintaining a high quality of information. It goes all the way from the acquisition of data and the implementation of advanced data processes, to an effective distribution of data.

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Ensuring Data Transformation Quality with dbt Core

Wayne Yaddow

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

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Making OT-IT integration a reality with new data architectures and generative AI

CIO Business Intelligence

Manufacturers have long held a data-driven vision for the future of their industry. It’s one where near real-time data flows seamlessly between IT and operational technology (OT) systems. Legacy data management is holding back manufacturing transformation Until now, however, this vision has remained out of reach.