Data Analytics

Data Analytics

Cloud analytics is a service model which provides elements of the data analytics process through a public or private cloud. Service providers follow a subscription-based, or utility (pay-per-use) pricing model while offering Cloud analytics applications and services. Analytics has six key elements to it. They are data sources, data models, processing applications, computing power, analytic models, and sharing or storage of results.

Cloud analytics is defined as any analytics initiative in which one or more of these elements are implemented in the cloud. Vendors, who offer cloud-based technologies that are designed to support a single element, refer to themselves as cloud analytics companies, which can cause confusion for potential users.

There are several cloud analytics products and services. Some examples of cloud analytics products and services include hosted data warehouses, software-as-a-service business intelligence (SaaS BI), and cloud-based social media analytics.

    • Software-as-a-service business intelligence (SaaS BI) is also known as on-demand BI, or cloud BI. SaaS BI involves delivery of business intelligence (BI) applications to end users from a hosted location. This model makes the setting up process easier and cost effective with the model also being extremely scalable as per the business needs of the client.

    • Cloud-based social media analytics offers the remote provisioning of tools. These tools include applications that can be used to select social media sites that best serve your purpose. It also has a separate application for harvesting data, storage services, and data analytics software.

  • A hosted data warehouse is a centralized repository for enterprise data. It is operated by the service provider, rather than being located on the enterprise’s own systems and made available to users from a remote location.

All enterprises must make sure they have fully grasped the extent of what’s involved, before they invest in cloud analytics. If they happen to invest without getting to know it fully, they may face the danger of going through it without actually understanding its scope. Although an investment in cloud analytics is considered profitable for the organisation, it requires proper planning to ensure that all six analytic elements are covered.

Advantages of Cloud analytics

    • It is quicker to adopt – Cloud based applications are easy to adopt and use. It does not require special skills or extensive training, and can be self-taught.

    • It lowers cost of total ownership – Less cost is incurred on maintenance, upgrades, and migrations, as opposed to on-premise analytics platforms.

    • Elasticity – Companies have the luxury of scaling up or scaling down.

    • Scalability – Companies have the luxury of seamless scaling up or scaling down process without affecting the operations of the organization.

    • Better collaboration – All the members of the team are able to share, discuss, and collaborate better using cloud analytics.

  • Sturdy data foundation – Can easily feed, consolidate and cleanse data. Since analytics and operations are running on top of the same data foundation, there is no mismatch, or information gap between these two.