Remove Backup Remove Data Center Remove Data Engineering
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Practical Steps for Enhancing Reliability in Cloud Networks - Part I

Kentik

However, arriving at specs for other aspects of network performance requires extensive monitoring, dashboarding, and data engineering to unify this data and help make it meaningful. When backup operations occur during staffing, customer visits, or partner-critical operations, contention occurs.

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Data Migration: Process, Types, and Golden Rules to Know

Altexsoft

In general terms, data migration is the transfer of the existing historical data to new storage, system, or file format. It involves a lot of preparation and post-migration activities including planning, creating backups, quality testing, and validation of results. What makes companies migrate their data assets.

Data 104
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The value of CDP Public Cloud over legacy Hadoop-on-IaaS implementations

Cloudera

Finally, IaaS deployments required substantial manual effort for configuration and ongoing management that, in a way, accentuated the complexities that clients faced deploying legacy Hadoop implementations in the data center. The case of backup and disaster recovery costs . Technology Component for Backup and Disaster Recover.

Cloud 86
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Discover and Explore Data Faster with the CDP DDE Template

Cloudera

Although not elaborated on in this blog post, it is possible to use a CDP Data Hub Data Engineering cluster for pre-processing data via Spark, and then post to Solr on DDE for indexing and serving. The solr.hdfs.home of the hdfs backup repository must be set to the bucket we want to place the snapshots.

Data 71
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Data Gravity in Cloud Networks: Achieving Escape Velocity

Kentik

In an ideal world, organizations can establish a single, citadel-like data center that accumulates data and hosts their applications and all associated services, all while enjoying a customer base that is also geographically close. San Diego was where all of our customer data was stored.

Network 59
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What is Data Pipeline: Components, Types, and Use Cases

Altexsoft

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. a data lake) doesn’t meet your needs or if you find a cheaper option.

Data 76
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Seeking Sustainable IT? Use Data Virtualization

TIBCO - Connected Intelligence

That means 85% of data growth results from copying data you already have. Granted, you need backups, but even if you back up all your new data twice, you still consume 50% more energy to store all the other extra copies. The primary driver behind data’s growth is business’ reliance on data as fuel for analytical insight.