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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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5 recommendations to get your data strategy right

IBM Big Data Hub

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. The evolution of a multi-everything landscape, and what that means for data strategy.

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Employing IoT to Boost Business

TDAN

IoT has a lot more to offer than merely establishing connections between systems and devices. IoT is paving ways for new services and products, which were just a figment of our imagination up until a […].

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SoftBank Selects Cloudera Data Platform to Leverage Customer Intelligence While Ensuring Data Security

Cloudera

The company also provides a variety of solutions for enterprises, including data centers, cloud, security, global, artificial intelligence (AI), IoT, and digital marketing services. Supporting Data Access to Achieve Data-Driven Innovation Due to the spread of COVID-19, demand for digital services has increased at SoftBank.

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Achieving Trusted AI in Manufacturing

Cloudera

According to Gartner , 80 percent of manufacturing CEOs are increasing investments in digital technologies—led by artificial intelligence (AI), Internet of Things (IoT), data, and analytics. Manufacturers now have unprecedented capacity to collect, utilize, and manage massive amounts of data. That is a very low number.

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The power of remote engine execution for ETL/ELT data pipelines

IBM Big Data Hub

Transformation styles like TETL (transform, extract, transform, load) and SQL Pushdown also synergies well with a remote engine runtime to capitalize on source/target resources and limit data movement, thus further reducing costs. With a multicloud data strategy, organizations need to optimize for data gravity and data locality.

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What Stands Between IT and Business Success? Data Complexity

CIO Business Intelligence

IT teams grapple with an ever-increasing volume, velocity, and variety of data, which pours in from sources like apps and IoT devices. At the same time, business teams can’t access, understand, trust, and work with the data that matters most to them. Often, enterprise data ecosystems are built with a mindset that’s too narrow.

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