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Waking Up The World of Big Data

Sisense

The term “Big Data” has lost its relevance. The fact remains, though: every dataset is becoming a Big Data set, whether its owners and users know (and understand) that or not. Big Data isn’t just something that happens to other people or giant companies like Google and Amazon. Big Data Today.

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Data Lakes: What Are They and Who Needs Them?

Jet Global

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? All the while, your marketing team is relying on marketing automation or CRM software they find the most productive.

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The Future Of The Telco Industry And Impact Of 5G & IoT – Part II

Cloudera

In part 2 of the series focusing on the impact of evolving technology on the telecom industry, we sat down with Vijay Raja, Director of Industry & Solutions Marketing at Cloudera to get his views on how the sector is changing and where it goes next. This is the next big opportunity for telcos.

IoT 109
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Using Artificial Intelligence to Make Sense of IoT Data

BizAcuity

IoT is basically an exchange of data or information in a connected or interconnected environment. As IoT devices generate large volumes of data, AI is functionally necessary to make sense of this data. Data is only useful when it is actionable for which it needs to be supplemented with context and creativity.

IoT 56
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Reporting: Is it the Most Boring, Important Thing in Analytics?

Juice Analytics

Among all the hot analytics initiatives to choose from (big data, IoT, NLP, data storytelling, cognitive BI, GDPR), plain old reporting is what is considered the most important strategic initiative. But seriously, reporting? We’re guilty of gravitating to concepts that seems to have more curb appeal.

Reporting 115
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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 111
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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

Facing a constant onslaught of cost pressures, supply chain volatility and disruptive technologies like 3D printing and IoT. An inaccurate AI prediction in a marketing campaign is a minor nuisance, but an inaccurate AI prediction on a manufacturing shopfloor can be fatal. The manufacturing industry is in an unenviable position.