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The state of data quality in 2020

O'Reilly on Data

Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. Comparatively few organizations have created dedicated data quality teams. Adopting AI can help data quality.

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It’s 2025. Are your data strategies strong enough to de-risk AI adoption?

CIO Business Intelligence

Despite decades of investment in data management solutions, many continue to struggle with data quality issues, either through their failure to modernise legacy investments or through the outcomes of acquisitions and business decisions, which in either instance have led to data existing in multiple silos across their organisations.

Risk 111
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Data Governance as an Emergency Service

erwin

Data governance (DG) as a an “emergency service” may be one critical lesson learned coming out of the COVID-19 crisis. Where crisis leads to vulnerability, data governance as an emergency service enables organization management to direct or redirect efforts to ensure activities continue and risks are mitigated.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Data landscape in EUROGATE and current challenges faced in data governance The EUROGATE Group is a conglomerate of container terminals and service providers, providing container handling, intermodal transports, maintenance and repair, and seaworthy packaging services. Eliminate centralized bottlenecks and complex data pipelines.

IoT 101
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How companies are building sustainable AI and ML initiatives

O'Reilly on Data

In 2017, we published “ How Companies Are Putting AI to Work Through Deep Learning ,” a report based on a survey we ran aiming to help leaders better understand how organizations are applying AI through deep learning. Data scientists and data engineers are in demand.

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HEMA accelerates their data governance journey with Amazon DataZone

AWS Big Data

Initially, the data inventories of different services were siloed within isolated environments, making data discovery and sharing across services manual and time-consuming for all teams involved. Implementing robust data governance is challenging. The following diagram illustrates the architecture of both accounts.

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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

Under the federated mesh architecture, each divisional mesh functions as a node within the broader enterprise data mesh, maintaining a degree of autonomy in managing its data products. The following diagram illustrates the building blocks of the Institutional Data & AI Platform.