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Data Architecture and Strategy in the AI Era

Cloudera

But, even with the backdrop of an AI-dominated future, many organizations still find themselves struggling with everything from managing data volumes and complexity to security concerns to rapidly proliferating data silos and governance challenges.

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How to Manage Risk with Modern Data Architectures

Cloudera

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Up your liquidity risk management game Historically, technological limitations made it difficult for financial institutions to accurately forecast and manage liquidity risk.

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Modern Data Architecture for Telecommunications

Cloudera

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Why telco should consider modern data architecture. The challenges.

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Beyond Data Fabrics: Cloudera Modern Data Architectures

Cloudera

What used to be bespoke and complex enterprise data integration has evolved into a modern data architecture that orchestrates all the disparate data sources intelligently and securely, even in a self-service manner: a data fabric. Cloudera data fabric and analyst acclaim. Move beyond a fabric. Next steps.

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Transforming Data Architecture through Data Mesh and Striim

Striim

Data Mesh plays a vital role in managing data effectively and is a valuable asset for organizations looking to improve agility, intelligence, and success in their operations in today’s constantly evolving environment. It also allows experts to access data directly, making work faster and more productive.

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Breaking State and Local Data Silos with Modern Data Architectures

Cloudera

Data is the fuel that drives government, enables transparency, and powers citizen services. For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Data quality issues deter trust and hinder accurate analytics.

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5 Data Governance Best Practices

Precisely

Data governance is rapidly shifting from a leading-edge practice to a must-have framework for today’s enterprises. Although the term has been around for several decades, it is only now emerging as a widespread practice, as organizations experience the pain and compliance challenges associated with ungoverned data.