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National Grid’s energy transformation is fueled by IT

CIO Business Intelligence

Modernizing a utility’s data architecture. These capabilities allow us to reduce business risk as we move off of our monolithic, on-premise environments and provide cloud resiliency and scale,” the CIO says, noting National Grid also has a major data center consolidation under way as it moves more data to the cloud.

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Snowflake: Data Ingestion Using Snowpipe and AWS Glue

BizAcuity

In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes.

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3 Key Factors Influencing Data Center Modernization

CDW Research Hub

For organizations trying to get a better handle on their data so they can see how it affects their business outcomes, the digital age has accelerated the need for modernizing the data centers. IT is constantly under immense pressure to improve, scale, consolidate, and optimize applications to meet the needs of their end-users.

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Snowflake: Data Ingestion Using Snowpipe and AWS Glue

BizAcuity

Introduction In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. Data ingestion must be performant to handle large amounts of data.,

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Meet the newest Data Superheros: The Sixth Annual Data Impact Awards Finalists Are…

Cloudera

Here’s what a few our judges had to say after reviewing and scoring nominations: “The nominations showed highly creative, innovative ways of using data, analytics, data science and predictive methodologies to optimize processes and to provide more positive customer experiences. ” – Cornelia Levy-Bencheton. .”

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

For nearly a decade, it’s provided a venue for developers, data and ML engineers, data architects, data scientists, and others to acquire or hone skills, explore provocative ideas, and network with peers. The evolution of data engineering reflects this. New trends in data architecture and data services.

IoT 20