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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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Business Intelligence tools & use cases

Apiumhub

With more and more data available, it’s getting more difficult to focus on the information we really need and present it in an actionable way and that’s what business intelligence is all about. In this article we will talk about Business Intelligence tools, benefits & use cases. . What is Business Intelligence.

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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.

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Data Discovery Drives Business Intelligence

Datavail

You can’t have superior “Business Intelligence” (BI) without excellent data retrieval, organization, and management. Data discovery is an element of data management , and managing data is the fundamental concept underscoring the value of business intelligence.

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Building a Beautiful Data Lakehouse

CIO

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. This dual-system architecture requires continuous engineering to ETL data between the two platforms. On the other hand, they don’t support transactions or enforce data quality.

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Breaking State and Local Data Silos with Modern Data Architectures

Cloudera

Agencies are plagued by a wide range of data formats and storage environments—legacy systems, databases, on-premises applications, citizen access portals, innumerable sensors and devices, and more—that all contribute to a siloed ecosystem and the data management challenge. . Modern data architectures. Forrester ).

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

Altexsoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?