Why can’t Big Data do without Cloud Computing?

When we talk about Big Data we refer to a combination of data, more or less structured, collected by a company from which information can be extracted to be used in Machine Learning projects, predictive analysis and other advanced analysis applications.

Big Data can come from a myriad of different sources, such as business transaction systems, customer databases, medical records, mobile applications, social networks, scientific research repositories, machine-generated data and real-time sensors used in Internet Of Things environments, and much more.

Businesses use the Big Data accumulated in their systems to improve operations, provide better customer service, create customized marketing campaigns based on specific customer preferences and, in general, to increase profitability. A company that uses big data has a potential competitive advantage over its competitors, as they are able to make business decisions faster and more wisely, provided, of course, that the data is used effectively.

What is the difference between Big Data and Cloud Computing?

In practice, Big Data can provide companies with valuable information about their customers — information that can be used to refine marketing campaigns to increase customer engagement and conversion rates. The use of Big Data allows companies to become increasingly customer-centric by using historical and real-time data to evaluate the evolution of consumer preferences allowing, consequently, to update and improve their marketing strategies and become more sensitive to customer needs.

To analyze this huge amount of data it is essential to rely on Cloud Computing. Instead of storing files on a proprietary hard drive or local storage device, archiving via Cloud Computing allows you to save them to a database or remote media: as long as an electronic device has access to the web, it has access to data and programs software to run it. At the same time, users can store files and applications on remote servers and can access all data via the Internet regardless of where the user is physically located. Therefore, while Big Data refers to the amount of data, with Cloud Computing we mean the way in which this data is stored and processed.

Cloud Computing offers services to users on a pay-as-you-go model and vendors offer three main services:

• Infrastructure as a Service (IAAS): here the service provider offers the entire infrastructure as well as the associated maintenance activities;
• Platform as a Service (PAAS): in this service, the Cloud provider offers resources such as storage, runtime, queuing, database, etc. However, the responsibility for the activities related to configuration and implementation depends on the company that purchased the service;
• Software as a Service (SAAS): this service is the easiest because it provides all the settings and infrastructure necessary for the user’s needs.

How can Cloud Computing support Big Data analysis?

Big Data and Cloud Computing are two technologies that are merging bringing significant benefits for businesses. With Cloud Computing, it is possible to set up in a very short time an infrastructure with all the resources needed by the company that guarantees continuity of services without interruptions. The Cloud-based infrastructure is also extremely flexible and scalable and can dynamically expand to provide storage for ever-growing data according to the needs of the company. Furthermore, with Cloud Computing, the responsibility shifts to cloud providers and the company only has to pay for storage space and energy consumption.

The relationships between Big Data and Cloud Computing can be classified according to the types of service:

• IAAS in the Public Cloud: IAAS is a cost-effective solution, and by using this cloud service, Big Data services allow people to access unlimited storage and computing power. It is a very cost-effective solution for companies because the cloud service provider bears all the costs of managing the underlying hardware;
• PAAS in Private Cloud: PAAS providers incorporate Big Data technologies into their services, therefore, eliminating the need to manage the complexities of managing individual software and hardware elements, which is a real concern when dealing with terabyte-sized amounts of data;
• SAAS in Hybrid Cloud: The Hybrid Cloud is an excellent solution for conducting the analysis of social media data which, today, is an essential parameter for companies.

3 advantages of Cloud Computing for Big Data

By combining Big Data and Cloud Computing technologies, three fundamental advantages are obtained:

• Speed: the data processing speed in a Big Data / Cloud Computing system is extremely high and allows the company to perform processing using data in real time. The timeliness of processing allows the company to be highly responsive to the needs of its customers because it can make decisions much faster and more accurately than the traditional model.
• Savings: the Pay-per-user model of Cloud technology transforms capital expenditure (Capex — Capital Expenditure, the cost to develop or supply durable assets for the system) into operational expenditure (OPEX — Operating Expense, the cost necessary to manage the system) . This means avoiding investments in infrastructures that are now the responsibility of the service provider and paying only for what the company actually uses.
• Security and privacy: data security and privacy are two main concerns to keep in mind when dealing with corporate data especially when the application is hosted on a cloud platform. To ensure maximum security, Cloud data is stored and processed in a central location commonly known as a Cloud storage server. Normally the service provider and the customer sign a service level agreement (SLA) which guarantees maximum mutual trust.