Two main technologies are at the heart of IT today – Big Data (or Cloud Computing) and Big Data (or Big Data). Fundamentally, Big data is about the massive scale of data while Cloud computing is about infrastructure. Cloud technology and Big data offer a simplified approach to enterprise computing, which is why they are so popular. Amazon’s “Elastic Map Reduce”, for example, shows how Big Data processing can be made easier by Cloud Elastic Computes.
Combining both of these technologies can result in a positive outcome for organizations. Both technologies are still in their infancy, but the combination of them provides scalable and cost-effective solutions in big data analytics.
Can we really call Big data and Cloud computing a perfect match? There are plenty of data points to support it. There are also real-time problems to be aware of. We will be discussing both of these aspects in this blog. We assume that you are familiar with Big data and Cloud computing.
Learn Big data and Cloud computing from the introductory blogs to get a better understanding of these areas.
Relationship between Big Data and Cloud Computing
Both big data and cloud computing are both valuable technologies. Many businesses combine both of these technologies to reap greater business benefits. Both technologies are designed to increase revenue and lower investment costs. Cloud manages local software, while Big Data aids in business decisions.
Let’s begin with the basics of these two technologies!
Big Data and Cloud Computing
Big data is the massive structured, semi-structured, or unstructured data that is stored and processed for data analysis purposes. Five Vs are the five main aspects of Big Data.
Volume – The amount of data
Variation – Different types of data
Velocity – Data flow rate in the system
Value – The value of data based upon the information contained within
Veracity – Data confidentiality and availability
Cloud computing provides services to users using a pay-as you-go model. These services are the three main services offered by cloud providers.
Infrastructure as a Service
The service provider provides complete infrastructure and maintenance services.
Platform as a Service (PAAS).
The Cloud provider provides resources such as object storage, runtime, quuing, databases, and more. The consumer is responsible for the configuration and implementation tasks.
Software as a Service (SAAS).
This service is the most user-friendly, as it provides all the infrastructure and settings required for the platform.
Big Data and Cloud Computing Relationship ModelCloud Computing Role in Big Data
Based on the service types, Big Data and Cloud computing relationships can be classified:
IAAS in the Public Cloud
IaaS can be a cost-effective option. Big Data services, which utilize this Cloud service, allow people unlimited storage and compute power. This is a cost-effective option for enterprises, as the Cloud provider takes care of all the hardware management.
Private Cloud PAAS
PaaS vendors integrate Big Data technologies into their service. They eliminate the complexity of managing hardware and software elements, which can be a real problem when dealing with terabytes.
SAAS in Hybrid Cloud
Companies are now able to analyze social media data in order to improve their business analysis. SaaS vendors are a great platform to conduct the analysis in this context.
Big data is a rapidly evolving technology that is relatively new. Let’s look at some of the common Big Data Myths, and the Facts Behind them.
What is Big Data and Cloud Computing?
As you can see, Cloud enables “As a Service” by abstracting the complexity and challenges through a scalable, elastic self-service application. Big data requirements are the same for distributed processing of massive amounts of data that is abstracted away from end users.
Big data analysis in Cloud has many benefits.
Cloud technology has made big data analysis more efficient, resulting in better results. Companies prefer to do big data analysis in the Cloud. Cloud also allows you to combine data from multiple sources.
Big Data analysis is a very difficult job on infrastructure because the data comes in large volumes at different speeds and types that traditional infrastructures are unable to keep up with. Cloud computing allows us to scale up or down according to our needs.