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    Glossary
    Table of Content

    Cloud Analytics

    Cloud data analytics is an analytical process that consolidates and analyses the data that is stored in cloud environments to generate useful business insights. By utilizing vendor-managed infrastructure instead of on-premises servers, companies can effectively handle and analyze large quantities of data without requiring significant hardware investments.

    Types of Cloud Analytics

    • Public Cloud analytics: Public cloud analytics involves analysing data stored on anytime-accessible servers. Such cloud setup offers a multitenant architecture allowing multiple organizations to use the same resources and services, such as virtual machines, data storage, and data processing, without sharing data.
    • Private Cloud analytics: It uses a private infrastructure, located on-site or managed by an external provider. Though it offers many of the same benefits as public cloud analytics, how it differs from it is in terms of increased data security and management control (Though they require additional resources to scale and maintain).
    • Hybrid Cloud analytics: Hybrid cloud analytics integrate public and private cloud environments to provide a flexible solution. Here, non-sensitive data is processed and stored in the public cloud, while sensitive data with stricter governance or data sovereignty requirements is managed on-premises or in a private cloud. It offers the users with utilization of public cloud scalability while maintaining oversight of sensitive data with private cloud elements.

    Benefits of cloud analytics

      Data Storage and Processing

      Removing the necessity for costly hardware and maintenance typically associated with on-premises data centres. Cloud analytics enables businesses to easily store large quantities of data in public or private clouds, making access and management effortless.

      Scalability

      On-demand computing resources enable quick access to data and faster decision-making by adjusting storage or analytics capacity as needed. This is particularly beneficial for handling fluctuating workloads.

      Advanced Analytical tools

      To identify patterns, predict trends and generate insights from complex datasets.

      Cloud analytics often incorporates sophisticated algorithms, including artificial intelligence (AI) and machine learning (ML). This integration enhances decision-making processes across various industries, from finance to healthcare.

      Real time Data Access

      Users can access data from anywhere with an internet connection, promoting collaboration and timely decision-making. Many cloud analytics solutions offer self-service capabilities, allowing non-technical users to generate insights without needing deep analytical expertise.