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Re-Thinking the Storage Infrastructure for Business Intelligence

Infinidat

Re-Thinking the Storage Infrastructure for Business Intelligence. With digital transformation under way at most enterprises, IT management is pondering how to optimize storage infrastructure to best support the new big data analytics focus. Adriana Andronescu. Wed, 03/10/2021 - 12:42.

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Exploring MariaDB’s Storage Engine Options

Datavail

It supports many types of workloads in a single database platform and offers pluggable storage architecture for flexibility and optimization purposes. You can set up storage engines on a per-database instance or per-table basis. Here are some of the storage engines you can leverage in MariaDB for your development projects.

Storage 98
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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO

2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security. It’s About the Data For companies that have succeeded in an AI and analytics deployment, data availability is a key performance indicator, according to a Harvard Business Review report. [3]

Analytics 323
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Understanding Data-platform Needs to Support Network Observability

Kentik

With software architectures increasingly adopting distributed, cloud-based models , network infrastructures have become complex webs of virtual and physical devices. With storage metadata, data platforms offer engineers opportunities for additional insights into data access, resource allotment and capacity, performance, and more.

Network 52
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Tapping high-performance computing for new business value

CIO

As companies digitally transform and steer toward becoming data-driven businesses, there is a need for increased computing horsepower to manage and extract business intelligence and drive data-intensive workloads at scale. The challenge: making complex compute-intensive technology accessible for mainstream use.

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Innovative Manufacturers are Investing in these Advanced Technologies

CIO

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. This allows teams to receive and review business intelligence and make changes in near-real-time rather than waiting hours or days to glean insights from data. [2]

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5 hot IT budget investments — and 2 going cold

CIO

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). This should secure our business strategy for the next five years and longer.”

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