Remove data-and-analytics-processes-can-we-get-personal
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Data and Analytics Processes: Can We Get Personal?

David Menninger's Analyst Perspectives

Sure, there are some options built in — perhaps the same action can be initiated by either clicking on a button, selecting a menu item or invoking a keyboard short-cut. The problem is that when every variation needs to be coded into the system, the prospect of providing personalized software programs to every individual is impractical.

Analytics 130
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DataOps For Business Analytics Teams

DataKitchen

Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. In business analytics, fire-fighting and stress are common. Analytics Hub and Spoke.

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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 better price-performance than other cloud data warehouses.

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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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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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Commerce strategy: Ecommerce is dead, long live ecommerce

IBM Big Data Hub

In today’s dynamic and uncertain landscape, commerce strategy—what we might formerly have referred to as ecommerce strategy—is so much more than it once was. Done correctly, this process also contains critical activities that can significantly reduce costs and satisfy a business’ key metrics for success.

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How AI is helping the NFL improve player safety

CIO Business Intelligence

Like many other professional sports leagues, the NFL has been at the leading edge of data-driven transformation for years. One of those data sources is the Next Generation Stats System (NGS), which captures real-time location, speed, and acceleration data for every player.