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Telecom Network Analytics: Transformation, Innovation, Automation

Cloudera

One of the most substantial big data workloads over the past fifteen years has been in the domain of telecom network analytics. The Dawn of Telco Big Data: 2007-2012. Suddenly, it was possible to build a data model of the network and create both a historical and predictive view of its behaviour.

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Deep Learning Would Be Crucial Under Sanders’s Medicare for All System

Smart Data Collective

The effort is laudable and realistic, but he needs to come up with a solution to contain costs. Deep learning is likely to play an essential role in keeping costs in check. Bernie Sanders needs to talk more about ways that he can control costs before passing Medicare for All. This will be essential for all countries.

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Using Geographic Data To Create A Perfect Google Maps Radius

Smart Data Collective

Data precision has completely revamped our understanding of geography in countless ways. We also use big data to facilitate navigation. One of the tools that utilizes big data is Google Maps. The Emerging Role of Big Data with Google Analytics.

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A Guide To The Methods, Benefits & Problems of The Interpretation of Data

datapine

In fact, a Digital Universe study found that the total data supply in 2012 was 2.8 Based on that amount of data alone, it is clear the calling card of any successful enterprise in today’s global world will be the ability to analyze complex data, produce actionable insights and adapt to new market needs… all at the speed of thought.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

Snowflake integrates with AWS Glue Data Catalog to access the Iceberg table catalog and the files on Amazon S3 for analytical queries. This greatly improves performance and compute cost in comparison to external tables on Snowflake , because the additional metadata improves pruning in query plans. Partner Solution Architect at AWS.

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Structural Evolutions in Data

O'Reilly on Data

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

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How AWS Payments migrated from Redash to Amazon Redshift Query Editor v2

AWS Big Data

This solution reduced our operational cost of maintaining a third-party application and its infrastructure. If you have similar use cases and need to provide a web-based tool to your customers to explore data on your Amazon Redshift cluster, consider using Amazon Redshift Query Editor V2.