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Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

These data processing and analytical services support Structured Query Language (SQL) to interact with the 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.

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

Datasphere goes beyond the “big three” data usage end-user requirements (ease of discovery, access, and delivery) to include data orchestration (data ops and data transformations) and business data contextualization (semantics, metadata, catalog services).

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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. Four key challenges prevent them from doing so: 1.

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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

Institutional Data & AI Platform architecture The Institutional Division has implemented a self-service data platform to enable the domain teams to build and manage data products autonomously. The following diagram illustrates the building blocks of the Institutional Data & AI Platform.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

An extract, transform, and load (ETL) process using AWS Glue is triggered once a day to extract the required data and transform it into the required format and quality, following the data product principle of data mesh architectures. This process is shown in the following figure.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

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How to Implement Data Lineage Mapping Techniques

Octopai

Look for the Metadata. In order to perform accurate data lineage mapping, every process in the system that transforms or touches the data must be recorded. This metadata (read: data about your data) is key to tracking your data. Data Lineage by Tagging or Self-Contained Data Lineage.

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