Keys to Effective Data Visualization

Data visualization is central to big data analytics because the volumes of data involved are beyond the scale that can be effectively manually reviewed by humans. Data visualization provides techniques for quickly viewing, understanding, and identifying patterns in big data that can’t otherwise be reasonably absorbed by humans through detail inspection. Join our discussion and get insights on: Best practices in effective big data visualization. Transformations necessary to enable effective visualization. Visualizing patterns. Data discovery versus descriptive analytics visualization.
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Spotlight

OTHER ON-DEMAND WEBINARS

Data for the Clinical Journey: Pairing Analytics with Health Cloud for Data-Driven Success

All the stakeholders within the Health and Life Sciences Industry find the need for a complete view of the trends affecting their patients in addition to personal data and history. Healthcare providers, insurers, and agencies even while having different roles in delivering care tend to face many of the same challenges.
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The Software-Defined Data Center: A Foundation for Digital Transformation

tierpoint

As reported in Forbes last year, 73% of companies are planning to move to a fully software-defined data center within two years. A software-defined data center is based on a virtualized environment of compute, storage, networking and security in conjunction with policy-based management and automation. The evolution from a traditional data center architecture to one that is software-defined can take months if not years but can yield immense benefits for the business. Join us for a discussion on the progress toward the fully software-defined data center, including benefits of infrastructure as code and overcoming challenges associated with traditional workflows.
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Applying Convolutional Neural Networks with TensorFlow

Databricks

In this latest Data Science Central Deep Learning Fundamentals Series webinar, we will cover the fundamentals behind TensorFlow and how to apply them within a convolutional neural network (CNN) example. The principles we will cover include CNN concepts and their impact to the accuracy and loss of your network. All these concepts will be brought to life by demonstrating how Databricks simplifies deep learning - letting you quickly access ready-to-use ML environments, as well as prepare data, and train models faster. After this session, if requested, you will receive the presentation and associated notebooks so you can run the samples yourself.
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Make Big Data Work in the Cloud

waterlinedata.com

As companies shift their Big Data to the cloud and hybrid environments, the need for Big Data analytics and a corresponding long-term analytics strategy has become increasingly critical. Here’s your opportunity to listen to experienced Big Data practitioners articulate their best practices in building successful, long term analytics architectures.
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