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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

One of the primary drivers for the phenomenal growth in dynamic real-time data analytics today and in the coming decade is the Internet of Things (IoT) and its sibling the Industrial IoT (IIoT). One group has declared , “IoT companies will dominate the 2020s: Prepare your resume!” trillion by 2030. trillion by 2030.”.

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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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How the Edge Is Changing Data-First Modernization

CIO Business Intelligence

From the factory floor to online commerce sites and containers shuttling goods across the global supply chain, the proliferation of data collected at the edge is creating opportunities for real-time insights that elevate decision-making. billion connected IoT devices by 2025, generating almost 80 billion zettabytes of data at the edge.

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How ASEAN Retailers Can Become insight driven with a Hybrid Cloud data strategy

Cloudera

As customers shift online, the data trails they leave behind, through email opens, click-throughs, preferred member programs, can help retailers provide personalized insights on a level like never before. The post How ASEAN Retailers Can Become insight driven with a Hybrid Cloud data strategy appeared first on Cloudera Blog.

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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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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.