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CIOs are rethinking how they use public cloud services. Here’s why.

CIO Business Intelligence

Over the past few years, enterprises have strived to move as much as possible as quickly as possible to the public cloud to minimize CapEx and save money. As VP of cloud capabilities at software company Endava, Radu Vunvulea consults with many CIOs in large enterprises. Are they truly enhancing productivity and reducing costs?

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

AWS Big Data

This integration enables our customers to seamlessly explore data with AI in Tableau, build visualizations, and uncover insights hidden in their governed data, all while leveraging Amazon DataZone to catalog, discover, share, and govern data across AWS, on premises, and from third-party sources—enhancing both governance and decision-making.”

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Why Enterprise Data Lineage is Critical for the Success of Your Modern Data Stack

Octopai

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

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The importance of data ingestion and integration for enterprise AI

IBM Big Data Hub

Data ingestion must be done properly from the start, as mishandling it can lead to a host of new issues. The groundwork of training data in an AI model is comparable to piloting an airplane. ELT tools such as IBM® DataStage® facilitate fast and secure transformations through parallel processing engines.

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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. This model balances node or domain-level autonomy with enterprise-level oversight, creating a scalable and consistent framework across ANZ.

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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

No, its ultimate goal is to increase return on investment (ROI) for those business segments that depend upon data. With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. date, month, and year).

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Addressing the Three Scalability Challenges in Modern Data Platforms

Cloudera

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).