What Are the Key Advantages and Drawbacks of Using the Cloud for Big Data?

 

Key Advantages and Drawbacks of Using the Cloud for Big Data?

Big data is the IT industry's buzzword. Organizations of all sizes recognize the significance of data and use it to measure success. Big data can also assist in identifying issues and identifying new chances for growth. 

  • There is no arguing that big data has tremendous advantages.  To add big data to your enterprise system, you will need a lot of computing resources and advanced software tools. 

  • Cloud enables organizations to make significant progress in meeting the demand for big data. 

  • It provides unlimited computing resources, making big data in the cloud initiatives a viable option for organizations of all sizes.


Cloud-based big data

Big data and computation are two different concepts. They are inextricably linked in the field of IT.

  • Big data refers to large amounts of data generated in an organization in various forms. They may be structured, semi-structured, or unstructured and may come from various sources. 

  • Big data also refers to the analysis of large amounts of data to solve a problem or identify a trend.

  • Various mathematical methods are used to analyze big data. The method of analysis varies depending on the type and source of data and the purpose of the study.


Cloud computing provides enterprises with computing resources and services that are available on demand. Indeed, the necessary infrastructure and storage resources are simply available. In the cloud, experts can do extensive studies. The cloud provides access to an infinite number of resources across the public cloud. 


  • These resources can be exploited for as long as they are required, and the ecosystem can be abandoned thereafter. Companies will only have to pay for the resources and services that they utilize.

  • A cloud provides on-demand resources and services. It means that firms are not required to create, own, or maintain infrastructure.

  • As a result, the cloud makes big data technology accessible and affordable to businesses of all sizes.


The Advantages of Big Data on the Cloud

The cloud provides numerous substantial benefits to enterprises of all sizes. The following are some of the most immediate and significant advantages of big data on the cloud.


Scalability

A typical business data center has various constraints when it comes to managing physical space, power, and cooling. They'll also need money to buy and deploy the hardware needed to develop a big data infrastructure. 

  • In comparison, a public cloud can manage tens of thousands of servers dispersed over numerous worldwide data centers. 

  • Companies might benefit from easily accessible infrastructure and software services. 

  • They can quickly build any infrastructure for data projects of any size.


Agility

Every data project is unique. While one project may require 100 servers, another may require twice that amount. Companies can deploy the resources required to fulfill their objectives with the help of the cloud. When the assignment is completed, it can be released.


Budget

The cost of establishing a commercial data center is considerable. In addition to hardware, firms must invest considerably in facilities, power, and ongoing maintenance. All of these costs are combined in the cloud into a flexible pay-per-use approach.


Resilience

In terms of value, data is at the heart of big data projects. As a result, the benefit of cloud resilience is data storage reliability. Clouds are built to replicate data and provide high availability across all resources.

The Drawbacks of Cloud-Based Big Data

Public clouds and numerous third-party big data services have a stellar track record in big data use cases. However, the cloud isn't all about advantages. Businesses must also consider the potential disadvantages.


Network Dependence

Cloud users rely heavily on network access from the LAN. Outages along the network path can result in increased latency or, in the worst-case scenario, complete inaccessibility. An outage may not affect a big data project, but it can be disastrous for users.


Storage Fees

Cloud data storage can result in significant long-term costs for large data projects. The three most important factors are data storage, migration, and retention. 

  • Loading big amounts of data onto the cloud may take a long time. In addition, there is a monthly price for storage instances.

  • Any additional relocation may result in increased costs for businesses. Keeping redundant data costs money. 

  • To better control cloud storage costs, businesses must have proper data retention and erasure policies in place.


Security

Big data in big data initiatives may have proprietary issues that fall under data protection and other restrictions. Users must take necessary precautions to ensure optimal data security in cloud storage. This includes authentication, authorization, and encryption while in storage or transit.

Standardization Deficiency

There is no standard approach to implementing or running a cloud-based big data deployment.

  • This might lead to poor performance and put the company at risk. All big data architectures require appropriate documentation. 

  • Care must also be taken to ensure that policies and procedures are followed.

Conclusion

If you want your company to be competitive, you must use big data in a cloud solution. It is critical to select the appropriate cloud deployment model. There are four types to choose from: public, private, hybrid, and multi-cloud. It's also critical to grasp the nature and tradeoffs of each model.


  • The private cloud provides greater control, but it is more expensive because a company must own and run the entire infrastructure. 

  • The public cloud combines the advantages of on-demand resources and scalability. 

  • However, users are in control of managing cloud resources and services. When pooling resources, a hybrid cloud is advised. 

  • They are, however, difficult to construct and manage. Multiple clouds provide advantages in terms of availability and cost.

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