Business Intelligence Data Center Network Storage 
CIO
JANUARY 12, 2023
The Lowdown on Edge Computing As new enterprise IT infrastructure deploys at the edge instead of in corporate data centers, there’s one main trigger for this shift. Here’s how edge computing works: a percentage of storage and compute resources move closer to the source of the data and away from the data center.
CIO
FEBRUARY 13, 2023
This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). These network, security, and cloud changes allow us to shift resources and spend less on-prem and more in the cloud.”
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CIO
JANUARY 26, 2023
For the freight transportation company, business intelligence (BI) is one area where IT can have a top-line impact. “We The vision of having 100% cloud infrastructure enabled us to significantly reduce our third-party data center costs as we migrated it into our cloud environment.” What storage do we have?’
Apps Associates
OCTOBER 8, 2021
Capsule summary: Architect and create data center in AWS GovCloud to host mission-critical ERP environment centered on Oracle E-Business Suite and Agile enterprise applications, other related applications, databases and tech stack across multiple environments (production, non-production) with disaster recovery and backup.
Apps Associates
JULY 14, 2023
Capsule summary: Re-architect and migrate North America Operations across 3 data centers (USA, Canada) to AWS Cloud hosting environment including all compute, network, storage, telecomm, mail exchange.
Apps Associates
APRIL 20, 2022
Mood Media is utilizing Apps Associates Managed Services for their AWS network, systems, databases, and EBS system. Apps Associates Managed Services for ongoing support and maintenance of the AWS Network, Operating Systems, Database, and Oracle ERP. . Designed infrastructure footprint for migration and implementation.
Xebia
JANUARY 19, 2023
– Jesse Anderson The data engineering field could be thought of as a superset of business intelligence and data warehousing that brings more elements from software engineering. That means the data engineering lifecycle comprises stages that turn raw data into a useful end product. Data disappears.
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