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Rapidminer Platform Supports Entire Data Science Lifecycle

David Menninger's Analyst Perspectives

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. Rapidminer Studio is its visual workflow designer for the creation of predictive models.

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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO Business Intelligence

Look at Enterprise Infrastructure An IDC survey [1] of more than 2,000 business leaders found a growing realization that AI needs to reside on purpose-built infrastructure to be able to deliver real value. 2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security.

Analytics 129
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Building a Beautiful Data Lakehouse

CIO Business Intelligence

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 102
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The Cloud Connection: How Governance Supports Security

Alation

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. Scheduling.

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Azure Data Sources for Data Science and Machine Learning

Jen Stirrup

LinkedIn uses Kafka is a way of processing data in real-time, and in vast amounts of data, well, we can imagine how many people are using LinkedIn at any one time, right? As you reach the end state itself, it’s very cost-effective for enterprises to move forward with open source analytics.

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

Scale the problem to handle complex data structures. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Some may ask: “Can’t we all just go back to the glory days of business intelligence, OLAP, and enterprise data warehouses?”

Metadata 105
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And the winners are…. Congratulations to the Sixth Annual Data Impact Awards winners

Cloudera

Enterprise Machine Learning: . AbbVie, one of the world’s largest global research and development pharmaceutical companies, established a big data platform to provide end-to-end operations visibility, agility, and responsiveness. Modern Data Warehousing: Barclays (nominated together with BlueData ). Technical Impact.