Nowadays, most of the companies face a huge challenge regarding data treatment and consumption. Information is everywhere, in every moment and in the most varied forms. The growth in the amount of data available has been exponential and will certainly not slow down. According to the International Data Corporation (IDC), data creation doubles in size every two years and it is expected that, by 2025, the digital universe (all data that is created and copied annually) will grow by up to 162 Zettabytes (ZB), or a trillion Gigabytes (GB). This volume is almost 10 times greater than the 16.2 ZB of data generated in 2016.
This growth was largely due to the rapid adoption of smart phones and devices worldwide over the past five years, with consumers creating huge amounts of data at home and on the go, in the form of posts in social media applications, photos and streaming.
It is estimated that there will be more than 6 billion smartphone users worldwide by 2020 and about 20.3 billion devices connected and in use by 2020 as the Internet of Things (IoT) continues to expand. By 2025, a person connected anywhere in the world will on average interact with devices connected almost 4,800 times a day, basically one interaction every 18 seconds. Apart from social media applications, it is estimated that by 2025, almost 20% of the data in the digital universe will be critical to people's daily lives, and almost 10% of that value will be hypercritical.
This is a rather frightening statistic, especially for companies that will have to deal with all this data volume, transform it into information and then use that information for their own advantage to make the most out of it at various levels (resource optimization, process improvements, deciding in the most appropriate way, taking advantage of new business opportunities and consequently increasing profitability).
If we look at a not too distant past, we easily realize that the adoption of a system of data analysis and support for decision making was quite complex to be implemented and maintained successfully because there were several factors that dictated this:
> Acquisition cost and maintenance of the system support infrastructure
> Cost of acquiring licensing for the various tools
> Cost of system expansion and functionalities
> Very limited or no collaboration functions
> Most of the tools demand the presence of highly specialized resources that needed a great learning curve to be able to take all the income from the system
Given this, how can companies adapt to this new reality where business is increasingly data driven? How can companies evolve in a sustained way and, at the same time, not lose the train of modernization, both processes and resources, allowing them to follow this escalation of information use in the daily life of the company? And how to combine this with budgets increasingly tight and little given to spending on innovation and development. The response from major vendors turned out to be based on a technology that is increasingly in vogue and expanding: the "Cloud", which is clearly revolutionizing the treatment and access to information.
The "Cloud" is no longer just a soundbite to be more present in our daily lives. Since the Cloud was primarily used by non-professional users, it took only a couple of years for the business layer to begin to take the cloud technology seriously and all the benefits that could come from it. The topic "Cloud" was for a time a taboo subject for most companies because the issues of security and persistence of information were not as clear as the desirable one so that its adoption was almost immediate. We must not forget that adopting "Cloud" technology, whatever it may be, we are putting into the hands of third parties something that, until then, would belong to the company and, as such, would always be accessible and controllable.
Taking advantage of this platform, the main players in the market quickly realized their potential in data analysis and processing and quickly put into practice a new concept, "Cloud Analytics".
HOWEVER, WHAT IS "CLOUD ANALYTICS"?
"Cloud Analytics" is a set of services that are "turnkey" to companies so they can capture, treat, view, analyze, predict, and collaborate on your data right from the start. In this type of service, the entire hardware component is the responsibility of the service provider, that is, installation, maintenance and repair is completely transparent to the customer and is only in charge of defining the desired processing / storage capacity to assemble the "Cloud Analytics" system. This solution is a winning option for both the supplier and the customer because it reduces the operational and maintenance costs to both parties; the supplier sees its operating costs reduced by using a single infrastructure that will support multiple customers, thereby offering a much more attractive price to the customer than in a traditional system. The customer, in addition to obtaining a lower cost provided by the most advantageous conditions of the supplier, can eliminate a series of quite high costs related to the operation and maintenance of these systems.
In addition to all hardware management being a vendors responsibility, one of the major advantages of Cloud Analytics systems is the existence of a panoply of solutions that are available out-of-the-box and that allow everybody to start analyzing and solving most common business questions in what is related with data analysis. As an example, we have:
> Extract, Transform and Load data (ETL)
> Churn Analysis
> Customer Lifetime Value
> Customer Segmentation
> Treatment and Analysis of Big Data
> Machine Learning
> Stream Analysis
These are just a few examples of solutions that have to be implemented from scratch and that would certainly bring many headaches and would clearly consume time and resources, two goods that are quite precious today. With this type of services, it is quite simple and intuitive to start producing results with the added advantage that the company that hires the services can choose the right time to resize your system without additional worries. Even for the most skeptical, it is always possible to opt for a hybrid solution where some systems reside in the sphere of the company and other systems reside in the Cloud of the service provider.
With the massification of this type of solutions, there has also been an equal increase in the level of information consumers. Nowadays, it is perfectly possible to ensure a Data Analytics system in the Cloud and soon after a relatively short period (days) users are exploring the system to the fullest of their capabilities because the entire education system on these platforms is also changed to respond to this constant demand for more information and knowledge. It is now extremely easy to acquire web-based knowledge about systems / tools, either through official vendors or through knowledge sharing forums.
Another perspective from which we can see the implications of Cloud Analytics systems is the use by small and medium-sized companies: until then, it was extremely complicated for a smaller company to be able to acquire, maintain and obtain revenues from Data Analytics systems because its costs were very high for the potential results that could occur. Nowadays, any company, however its size, can count on the help of these systems at a much more sustained cost and according to their reality.
We conclude that this is really the way without turning back. A recent study by Dresner Advisory Services came to a quite interesting conclusion, not only on the evolution of this type of platforms, but also on the trends that will lead the market to bet more and more on these solutions. The study was carried out with representatives of the various business / activity areas.
The main conclusions of the study were:
> The adoption of Cloud Analytics systems is going up, doubling the values of 2016.
> Over 90% of Sales and Marketing teams indicate that Cloud Analytics systems will be essential to produce their work.
> 66% of organizations that consider themselves successful in what relates to the topic of Analytics are using tools in the Cloud.
> The highest adoption rates for Cloud Analytics systems are in Financial Services (62%), Technology (54%) and Education (54%).
> 86% of entities that have adopted the Cloud Analytics system point to Amazon AWS as their first choice, 82% to Microsoft Azure as the second choice, 66% to Google Cloud and 36% to IBM Bluemix.
> The importance of Cloud Data Analytics systems continues to accelerate in 2018, with most respondents considering it a vitally important element in their most comprehensive analytics strategy.
> The Sales and Marketing departments lead the ranking of departments that use / plan to use the short-stretch Cloud Analytics solutions. Business Intelligence Competency Centers (BICC) are second place with an adoption rate of 60%.
> The most requested features in Cloud Analytics systems are:
o Advanced Visualizations
o Ad-hoc query
o Data Integration
It is interesting to note that the Manufacturing industry has the greatest interest in Dashboards, Ad-hoc query, Production Reports, Research Interfaces, Location Intelligence and direct writing capability in transactional systems.
As we can verify, we are facing a new reality that has come to stay. The massive use, especially by the main and more complex areas (financial services) is a realization of this fact.
Clearly, Cloud Analytics solutions are democratizing an entire data-driven culture and revolutionizing the world of lower-cost business analytics, faster deployment, and product review. With the right guidance, creating a data-driven culture is now easier and less expensive than ever before! Tomorrow is now!