Beginner’s Guide to Cloud Analytics In 4 Simple Points

Introduction

If you are someone who is interested in the Cloud COmputing domain, you must’ve heard about Cloud Analytics. Cloud Analytics in the Cloud Computing domain is gaining popularity swiftly. Cloud Analytics uses the Cloud server to perform Data Analytics in Cloud Computing. This Cloud server is either public or private. A third party provides the Cloud Analytics platform to organizations that cannot afford a storage facility on their premises.

This blog will help you know more about Cloud Computing Analytics so that you can easily find your way as a Cloud Computing enthusiast.

1. Definition Of Cloud Data Analytics 
2. Why Use Cloud Analytics?
3. How Does Cloud Analytics Work?
4. What Are Cloud Analytics Tools?

1. Definition Of Cloud Data Analytics 

Cloud Analytics uses Cloud storage as a Software as a Service (SaaS) model for Business Intelligence. Other features in Cloud Analytics can be derived through the Platform as a Service (PaaS) tool. 

Apart from on-demand Business Intelligence, Cloud Analytics services have other advantages like cost-effectiveness and the burden of on-site servers. 

Organizations have the option of choosing Cloud storage based on requirements. An organization can choose their Cloud storage in three ways:

1. Public Cloud –  Multiple users publicly share the network system. The data remains private. It follows a multi-tenant architecture to share Cloud storage with other organizations. 
2. Private Cloud – Both the IT system and the data remains private to only one organization. This is recommended for organizations that require very high security. If your organization has more concerns about the information and security, you can choose a private Cloud.
3. Hybrid Cloud – It is a combination of a public and a private Cloud. An organization saves sensitive data on a small scale using a hybrid Cloud.

2. Why Use Cloud Analytics?

There are numerous advantages of Cloud Analytics. Firstly, Cloud Computing gives remote access and vast storage. Secondly, it is called Cloud-based Data Analytics as all the essential Business Intelligence operations and processes are done on the Cloud.

1. Flexibility – Accessing real-time data quickly is a significant advantage in making an informed decision through the valuable insights derived from Data Analytics tools. Expanding the service is considerably more comfortable as organizations are free from on-services in a rigid environment.
2. Data collection and consolidation – The Internet collects a myriad of data every millisecond. This collected data is consolidated before the analysis. With Cloud Analytics, Data Consolidation is easy because it is accessible and flexible. Cloud-based Data Consolidation makes data mining easy for building a real-time prediction model.
3. Customization and Scalability – Cloud Analytics efficiently solves scalability issues. The Cloud-service provider makes easy customization possible to expand storage.
4. Agility – As the number of users increases, the Cloud becomes versatile and smart to adapt to high demands. This enables the business to act immediately when data scaling and leveraging occurs based on market values. Integration of resources and the ability to find answers quickly is a major advantage of Cloud Analytics.

We have mentioned some other features of Cloud Analytics below:

1. It follows a unified approach to process the data resulting in quick accessibility.
2. Cross-functional teams easily collaborate on the same data. Insights are effortlessly shared among the employees and progress monitoring is seamless.
3. Governance over the consolidated data is controlled. Data security increases with Cloud Computing and Analytics. The control over the data access is extensively strict. It assigns access rights to users.

3. How Does Cloud Analytics Work?

Analyzing social media data is a basic Cloud Analytics application. Most organizations prefer Cloud Analytics for comprehending their web traffic because the data is immediately available for analysis. 

Third-party Cloud service providers like Microsoft, Google, and Amazon provide Cloud spaces for all organizations. The collected data is stored in the Cloud space purchased from the Cloud service provider. The powerful servers hold many Data Analytics tools. 

Collected data is stored in the Cloud server that can be retrieved later. The Data Analytics tool analyzes the data for useful insights. The architecture follows six elements to implement the Cloud Analytics system.

1. The data is collected from Data Sources.
2. Data Models are structures that relate to the collected data.
3. Processing applications where large amounts of data are processed in the warehouse (Data Warehousing).
4. Computing power analyzes the ingested data.
5. Analytical models are mathematical models that predict the outcome.
6. Data sharing and storage enables easy sharing and scaling.

The stored data is safe in the Cloud during natural disasters or the sudden crashing of local computers. 

4. What Are Cloud Analytics Tools?

Cloud Analytics tools assist in ingesting, storing, and analyzing the data. They produce a report in an understandable format. Various such tools are readily available in the market. A few of them, for instance, are Microsoft’s Power BI, IBM Cognos Analytics, and Domo. These tools collect and analyze data and provide Cloud-based Data Analytics. 

Conclusion

Cloud Analytics is a disruptive method in Data Analysis and Business Intelligence. Organizations are widely adopting Cloud Analytics for social media analysis and tracking website traffic.

If you wish to learn more about Cloud and Analytics, Jigsaw Academy’s Postgraduate Certificate Program In Cloud Computing will be of help. This is a 6-month-long online course, taught by industry experts and SMEs, which will aid you in becoming a complete cloud professional!

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• Top 10 Major Characteristics of Cloud Computing