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Google BigQuery Architecture for Data Engineers

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Google’s BigQuery is an enterprise-grade cloud-native data warehouse. BigQuery was first launched as a service in 2010, with general availability in November 2011.

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Here’s Why Automation For Data Lakes Could Be Important

Smart Data Collective

Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation. In order for this to even be possible, the data visualization aspect needs to be streamlined to show exactly what the user wants to see.

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Automating Model Risk Compliance: Model Validation

DataRobot Blog

When the FRB’s guidance was first introduced in 2011, modelers often employed traditional regression -based models for their business needs. In addition to the model metrics discussed above for classification, DataRobot similarly provides fit metrics for regression models, and helps the modeler visualize the spread of model errors.

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Themes and Conferences per Pacoid, Episode 5

Domino Data Lab

The program supports hands-on data science class sizes of more than 1,200 students based on JupyterHub , and this sets a bar for enterprise infrastructure. This is also the case for a large segment of enterprise which must take competition and security concerns seriously. Data visualization for prediction accuracy ( credit: R2D3 ).

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. for DG adoption in the enterprise.

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How Zurich Insurance Group built a log management solution on AWS

AWS Big Data

Develop log and trace analytics solutions with interactive queries and visualize results with high adaptability and speed. Austin Rappeport is a Computer Engineer who graduated from the University of Illinois Urbana/Champaign in 2011 with a focus in Computer Security.

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Accomplish Agile Business Intelligence & Analytics For Your Business

datapine

It’s necessary to say that these processes are recurrent and require continuous evolution of reports, online data visualization , dashboards, and new functionalities to adapt current processes and develop new ones. The term “agile” was originally conceived in 2011 as a software development methodology.