Remove Data Strategy Remove Data Transformation Remove Metadata
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Data Catalog Role in Data Transformation and Governance

TDAN

Nearly every data leader I talk to is in the midst of a data transformation. As businesses look for ways to increase sales, improve customer experience, and stay ahead of the competition, they are realizing that data is their competitive advantage and the key to achieving their goals. And it’s no surprise, really.

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Automate discovery of data relationships using ML and Amazon Neptune graph technology

AWS Big Data

We took this a step further by creating a blueprint to create smart recommendations by linking similar data products using graph technology and ML. In this post, we showed how an organization can augment a data catalog with additional metadata by using ML and Neptune with an automated process.

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Sure, Trust Your Data… Until It Breaks Everything: How Automated Data Lineage Saves the Day

Octopai

This challenge is especially critical for executives responsible for data strategy and operations. Here’s how automated data lineage can transform these challenges into opportunities, as illustrated by the journey of a health services company we’ll call “HealthCo.” This is where Octopai excels.

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Fabrics, Meshes & Stacks, oh my! Q&A with Sanjeev Mohan

Alation

We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases. But, through it all, Mohan says it’s critical to view everything through the same lens: gaining business value from data. Data fabric is a technology architecture.

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Tackling AI’s data challenges with IBM databases on AWS

IBM Big Data Hub

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging.

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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

This post explores how the shift to a data product mindset is being implemented, the challenges faced, and the early wins that are shaping the future of data management in the Institutional Division. The following diagram illustrates the building blocks of the Institutional Data & AI Platform.

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Expanding data analysis and visualization options: Amazon DataZone now integrates with Tableau, Power BI, and more

AWS Big Data

Publish data assets – As the data producer from the retail team, you must ingest individual data assets into Amazon DataZone. For this use case, create a data source and import the technical metadata of four data assets— customers , order_items , orders , products , reviews , and shipments —from AWS Glue Data Catalog.