Remove insights cloud-data-analytics real-time-data-analytics
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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. It appears that it’s AI everywhere all the time.

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A Look Back at the Gartner Data and Analytics Summit

Cloudera

All of that technology, though, depends on data to be successful. Here are a couple of the biggest takeaways we had from our time at the event. What we’ve seen is that more businesses are looking at the potential of those tools through the lens of trust—specifically, do I trust these open models with my data?

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

How to make smarter data-driven decisions at scale : [link]. The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. A lot has changed in those five years, and so has the data landscape. But if they wait another three years, they will never catch up.”

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Solving the Data Daze – Analytics at the Speed of Business Questions

Rocket-Powered Data Science

Data is more than just another digital asset of the modern enterprise. Leaders now require forward-looking insights for competitive market advantage and advancement. So, what happens when the data flows are not quarterly, or monthly, or even daily, but streaming in real-time? Access to data has done that.

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Power analytics as a service capabilities using Amazon Redshift

AWS Big Data

Analytics as a service (AaaS) is a business model that uses the cloud to deliver analytic capabilities on a subscription basis. This model provides organizations with a cost-effective, scalable, and flexible solution for building analytics. times lower cost per user and up to 7.9 Amazon Redshift delivers up to 4.9

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Reference guide to analyze transactional data in near-real time on AWS

AWS Big Data

Business leaders and data analysts use near-real-time transaction data to understand buyer behavior to help evolve products. The primary challenge businesses face with near-real-time analytics is getting the data prepared for analytics in a timely manner, which can often take days.

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Editorial Review of “Building Industrial Digital Twins”

Rocket-Powered Data Science

I was asked by the publisher to provide an editorial review of the book “Building Industrial Digital Twins: Design, develop, and deploy digital twin solutions for real-world industries using Azure Digital Twins“, by Shyam Varan Nath and Pieter van Schalkwyk. The digital twin is more than a data collector. Let us begin….