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Enter the next phase of Industry 4.0 with edge AI

CIO Business Intelligence

All kinds of things can be automated The question is, how should businesses go about modernising their own applications effectively? Generally speaking, a healthy application and data architecture is at the heart of successful modernisation.

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Companies to shift AI goals in 2025 — with setbacks inevitable, Forrester predicts

CIO Business Intelligence

The challenge is that these architectures are convoluted, requiring diverse and multiple models, sophisticated retrieval-augmented generation stacks, advanced data architectures, and niche expertise,” they said. They predicted more mature firms will seek help from AI service providers and systems integrators.

ROI 127
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Driving Success With a Modern Data Architecture and a Hybrid Approach in the Financial Services and Telco Industries

Cloudera

As my colleague Wim Stoop previously shared, “A well-planned enterprise data strategy helps companies get the most of their data, making it known, discoverable, available, trusted, and compliant. This does not mean ‘one of each’ – a public cloud data strategy and an on-prem data strategy.

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Data architecture strategy for data quality

IBM Big Data Hub

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

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Using Strategic Data Governance to Manage GDPR/CCPA Complexity

erwin

The complexity of regulatory requirements in and of themselves is aggravated by the complexity of the business and data landscapes within most enterprises. Creating and automating a curated enterprise data catalog , complete with physical assets, data models, data movement, data quality and on-demand lineage.

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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

A well-designed strategy can help organizations balance business growth with environmental, social and governance (ESG) responsibility while improving operational efficiency. For example, reducing redundant data storage or optimizing cloud resource usage can lead to financial and environmental benefits.

IT 59
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Deciphering the Pros & Cons of Real-Time Data Streaming

Smart Data Collective

It is essential to process sensitive data only after acquiring a thorough knowledge of a stream processing architecture. The data architecture assimilates and processes sizable volumes of streaming data from different data sources. This very architecture ingests data right away while it is getting generated.

IoT 134