The combination of the two has brought beneficial results to the organization. Needless to say, both technologies are in the development stage, but their combination takes advantage of scalable and cost-effective solutions in big data analysis.
So, can we say that big data and cloud computing are perfectly combined? Well, there are data points to support it. In addition, there are some real-time challenges to deal with.
The relationship between big data and cloud computing
Both big data and cloud computing technologies are valuable in themselves. In addition, the goal of many enterprises is to combine the two technologies to obtain more commercial benefits. Both technologies aim to increase the company's income and reduce the investment cost. Although the cloud manages local software, big data helps business decisions.
Let's start with the basic overview of these two technologies!
Big Data and Cloud Computing
Big data processes a large number of structured, semi-structured or unstructured data for storing and processing data analysis. Big data has five aspects, which are described by 5V.
Quantity _ Data Quantity
Category _ Different types of data
Speed _ Data rate in the system
Value _ Data is based on the value of the information contained in it.
Accuracy _ data confidentiality and availability
Cloud computing provides services to users in a pay-as-you-go mode. Cloud providers provide three main services, which can be summarized as follows:
Infrastructure as a service (IAAS)
Here, the service provider will provide the whole infrastructure and maintenance-related tasks.
Platform as a service (PAAS)
In this service, cloud providers provide resources such as object storage, runtime, queues and databases. However, the responsibility for tasks related to configuration and implementation depends on the user.
Software as a service (SAAS)
This service is the most convenient service, it provides all necessary settings and infrastructure, and provides IaaS for the platform and infrastructure.
Relationship model between big data and cloud computing The role of cloud computing in big data
Please click to enter a picture description.
The relationship between big data and cloud computing can be classified according to the service type:
IAAS is in the public cloud.
IaaS is an economical and efficient solution. With this cloud service, big data services enable people to gain unlimited storage and computing power. This is a very economical and efficient solution for enterprises where cloud providers bear all the costs of managing basic hardware.
PAAS in private cloud
PaaS providers integrate big data technology into their services. Therefore, they eliminate the complexity of managing individual software and hardware elements, which is a real problem when dealing with TB-level data.
SAAS in Hybrid Cloud
Nowadays, analyzing social media data has become a basic parameter for companies to conduct business analysis. In this case, SaaS providers provide an excellent analysis platform.
What is the relationship between big data and cloud computing?
Therefore, from the above description, we can see that the cloud abstracts challenges and complexity through extensible and flexible self-service applications, thus realizing the "as a service" mode. When extracting massive data from end users for distributed processing, the demand for big data is the same.
Big data analytics in the cloud has several benefits.
Improved analysis
With the progress of cloud technology, big data analysis is more perfect and brings better results. Therefore, companies tend to perform big data analysis in the cloud. In addition, the cloud helps to integrate data from many sources.
Simplified infrastructure
Big data analysis is an arduous task in infrastructure, because the traditional infrastructure usually can't keep up with the large amount, high speed and many types of data. Because cloud computing provides a flexible infrastructure, we can expand it according to the needs at that time, so it is easy to manage the workload.
reduce costs
Both big data and cloud technologies create value for organizations by reducing ownership. Cloud's pay-per-user model transforms capital expenditure into OPEX. On the other hand, Apache reduces the licensing cost of big data, which should cost millions of dollars to build and buy. Cloud enables customers to process big data without large-scale big data resources. Therefore, both big data and cloud technology are reducing enterprise costs and bringing value to enterprises.
Security and privacy
When dealing with enterprise data, data security and privacy are two main issues. In addition, when your application is hosted on the cloud platform, it will become a major problem due to its open environment and limited user control security. On the other hand, a big data solution like Hadoop is an open source application, which uses a lot of third-party services and infrastructure. Therefore, today, system integrators have introduced flexible and scalable private cloud solutions. In addition, it also takes advantage of scalable distributed processing.
In addition, cloud data is stored and processed in a central location, which is often called a cloud storage server. Service providers and customers will sign service level agreements (SLA) with them to gain their trust. If necessary, the provider can also take advantage of the required advanced security control level. This ensures the security of big data in cloud computing, covering the following issues:
Protect big data from advanced threats.
How cloud service providers maintain storage and data.
Need to protect some rules related to service level agreements.
data
capacity
expansibility
safe
privacy
Availability of data storage and data growth
On the other hand, in many organizations, big data analysis is used to detect and prevent advanced threats and malicious hackers.
virtualization
Infrastructure plays a vital role in supporting any application. Virtualization technology is an ideal platform for big data. Virtualized big data applications like Hadoop have many advantages that physical infrastructure cannot achieve, but it simplifies big data management. Big data and cloud computing point out the convergence of various technologies and trends, which makes IT infrastructure and related applications more dynamic, more consuming and modular. Therefore, big data and cloud computing projects rely heavily on virtualization.