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Data Mining: The Knowledge Discovery of Data

Analytics Vidhya

Introduction We are living in an era of massive data production. When you think about it, almost every device or service we use generates a large amount of data (for example, Facebook processes approximately 500+ terabytes of data per day).

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LUX – Intelligence Visual Discovery of data using python

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post LUX – Intelligence Visual Discovery of data using python appeared first on Analytics Vidhya. Overview Introduction Introduction on the library lux Installation of lux.

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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.

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Introducing Native Connector for Google BigQuery: Boosting Data Lineage, Migration, and Discovery

Octopai

This new native integration enhances our data lineage solution by providing seamless integration with one of the most powerful cloud-based data warehouses, benefiting data teams and enabling support for a broader range of data lineage, discovery, and catalog.

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Driving Discovery and Experimentation in your Organization

Speaker: Teresa Torres, Product Discovery Coach, Product Talk, David Bland, Founder and CEO, Precoil, and Hope Gurion, Product Coach and Advisor, Fearless Product LLC

But to make progress, you can't let things slow to a crawl while you focus resources on gathering data. This is where continuous discovery and experimentation come in. We'll cover: Why discovery and experimentation are important. How to accept and mitigate risk. June 4, 2019 9:30 AM PDT, 12:30 PM EDT, 5:30 PM BST

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Data science as a catalyst for scientific discovery

O'Reilly on Data

Michelle Gill discusses how data science methods and tools can link information from different scientific fields and accelerate discovery. Continue reading Data science as a catalyst for scientific discovery.

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Data Makes Possible Many Things: Insights Discovery, Innovation, and Better Decisions

Rocket-Powered Data Science

In the early days of the big data era (at the peak of the big data hype), we would often hear about the 3 V’s of big data (Volume, Variety, and Velocity). Variety = the most rich V for insights discovery, innovation, and better decisions. The site’s domain name says it all: Data Makes Possible!

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Business Monitoring Systems: Using ML to Analyze Metrics

This whitepaper discusses how automated business monitoring solutions like Yellowfin Signals revolutionize the way users discover critical and relevant insights from their data. Download to learn: 5 business benefits of automated data discovery with ABM. The evolution of dashboards to automated business monitoring.

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How to Foster Data Culture (with Data Intelligence Technology!)

Speaker: Aaron Kalb, Co-Founder and CDAO at Alation

Given that, it probably sounds like Silicon Valley-hubris to suggest that technology can create data culture. Throughout history, however, technology has sparked cultural change, and today, data intelligence technology, like data catalog software, is helping enterprises develop data cultures.

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How to Foster Data Culture (with Data Intelligence Technology!)

Speaker: Aaron Kalb, Co-Founder and CDAO at Alation

Given that, it probably sounds like Silicon Valley hubris to suggest that technology can create data culture. Throughout history, however, technology has sparked cultural change, and today, data intelligence technology, like data catalog software, is helping enterprises develop data cultures.

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Best Practices for Creating Long-Lasting and Continuous Discovery Habits

Speaker: Teresa Torres, Internationally Acclaimed Author, Speaker, and Coach at ProductTalk.org

Industry-wide, product teams have adopted discovery practices like customer interviews and experimentation merely for end-user satisfaction. Data shows that the best product teams are shifting from this mindset to a continuous one. How to define a clear benchmark for what a strong continuous discovery team does.