Today there are two major issues at the heart of IT specifically and business in general: Cloud Computing, and the collection, analysis, and interpretation of big data.

In this post, we pose the question: are Cloud Computing and Big Data connected? Can they be combined in a deep way? Are they mutually reinforcing? The answer is yes, yes, and yes.

But that’s not enough, we want to go further, and investigate the advantages of combining these two technologies. We will identify the advantages that are already being realized and those that will be more established in the near future. First, let’s start by clarifying what the terms “Cloud Computing” and “Big Data” actually mean, by going beyond the simple “buzzwords.”


What is Cloud Computing?

Cloud computing is the distribution, via the internet, of essential services such as servers, databases, and software. In short, a provider provides users with on-demand access to services of storage, processing, and data transmission.

In this way, companies and individuals no longer need to download software on their computers or other devices to use certain programs or applications: they can do so in the cloud, from any location. Similarly, those same companies no longer have the need for on-site physical servers (nor the related costs of purchasing equipment, management, maintenance, and possible malfunction).

At first glance, you can see the enormous and multifaceted advantages that this technology offers, ranging from cost savings, increased efficiency, improved reliability and security, to the great flexibility and scalability (we discussed each of these aspects in this post).

It’s no surprise that, in a April 2018 report, Gartner noted that Cloud Computing will double its audience of users, and simultaneously its value, going from $153 billion in 2017 to $302 billion expected for 2021 (source). According to another analysis, this time conducted by LinkedIn, Cloud Computing related skills are the most requested by companies in 2019 (source).

In short, the data speaks for itself and it underlines how much (and why) this technology is at the center of the business and a top area of focus for companies at all levels, from start-ups to giants in various sectors, and at all latitudes. For today, but even more so, for tomorrow.


What is Big Data (and Smart Data or Deep Data)?

We’ve all heard of “Big Data” but what does the term really mean? 

Let’s start from a technical definition, provided by Gartner: “Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” 

Going a little deeper, Big Data allows you to apply modern tools to a historical challenge: really getting to know your customers and potential customers. It also allows you to have an understanding of your own business with a depth and breadth that was absolutely unthinkable before.

The consequence of all of this is the ability to put on track effective, targeted actions designed to improve the processes and structures of your company, and to improve relations with the ‘outside’. The benefits, in the final analysis, can affect the marketing, sales, purchasing, customer service, and human resources departments, in short: the entire structure and business processes. 

The analysis of Big Data is something that, in today’s ecosystem, is essential. However, we must avoid the mistake of limiting ourselves to indiscriminately collecting an enormous amount of information from all possible sources. This is because not all data is the same. Instead, it is necessary to be able to select – upstream and then downstream – the data most useful for your company, for its different purposes, with the utmost flexibility. 

That’s why today we prefer to talk about “Smart or intelligent” data, which differs from the masses because they bring “value,” are functional and significant. Some prefer to define this data as the most important, referring to it as “Deep Data” or “Good Data”; however, the substance does not change.


The advantages of combining Cloud Computing with Big Data analysis

Combining Cloud Computing and Big Data analysis brings enormous benefits and enhances the effectiveness of both these technologies, which can strengthen each other. This combination must be studied carefully, in all its various aspects, and above all must be calibrated “to measure,” depending on the needs of the individual company and its objectives, which may vary over time.

It is, therefore, essential to rely on specialized companies, such as Doxee, who has been working in this field for years with leading national and international organizations such as Enel, who recently migrated about 6,000 servers to the cloud (see this article).

Having made this fundamental premise, now we’ll look at the main advantages of the integration between Cloud Computing systems and Big Data analysis.


1. Significant savings in time and money

Buying and managing a data center that is large enough for effective Big Data analysis can be very expensive, not to mention the countless technical difficulties related to maintenance. In short, it is a huge investment in terms of costs, time, and specialized personnel. With the cloud, these responsibilities are shifted to the provider, which, in the vast majority of cases, has much greater know-how that is always up to date. On the other hand, the company buys these services on-demand in a pay-per-use model that reduces and optimizes costs.


2. Increased efficiency and flexibility

Let’s start with the initial stages: the installation and execution of a local server can take weeks. Then consider the rapid obsolescence of technologies in terms of storage and data management, which require continuous updates, incurring other inefficiencies and costs. With cloud computing, these problems are eliminated. Providers, in fact, can make the necessary infrastructure available in a short time and ensure that they are constantly updated.

Then there are the aspects of flexibility and scalability, which are absolutely central: in the cloud, storage space can be increased quickly, but also reduced, depending on the requirements of the business. When we talk about integration between the cloud and Big Data, we must never forget that they compose a virtuous circle: Cloud Computing systems make the analysis of data more efficient, and at the same time, they aid in the discovery of new data, in large volumes, from the most diverse sources, in an omnichannel and smart way. That’s why the most important and innovation-conscious companies in the world today rely almost entirely on the cloud. Think of AirBnB and Uber, who use such systems to handle complex issues related to their business coordination and the interfaces themselves. 


3. Security and privacy

Security and privacy are the most delicate and slippery issues when it comes to the collection and analysis of big data. Inattention, unexpected weaknesses in the infrastructure. or a failure to update the legal regulations in force can be enough to trigger real storms. Translated: such storms could result in a loss of turnover, loss of customers, and the collapse of loyalty and brand reputation. 

Stronger Cloud Computing service providers address these issues on a daily basis, with unmatched attention to individual companies. That’s why relying on them is the equivalent of ensuring maximum peace of mind on these thorny fronts.