A $189 billion worldwide market for Big Data and Business Analytics (BDAs) in 2019 according to IDC and a 12% increase leading to total revenues for BDAs worldwide of $274.3 billion. A steady growth, observed over the past years too, with a forecast for 2018-2022 of a five-year compound annual growth rate (CAGR) of 13.2%.
According to IDC, not only the revenues but also the data generated will grow, estimated for 2018 at 30 zettabytes, an amount tripled by 2023 when 100 zettabytes will be reached.
What makes the Big Data and BDA market grow more?
Assuming that digital transformation is an enabling factor for the analysis, and therefore for the use of data in business management, the most profitable segment in the BDA market is recorded by the IT services category with $77.5 billion, followed by hardware purchases ($23.7 billion) and business services ($20.7 billion). BDA software revenues will be $67.2 billion in 2019, divided between tools for generating data query and reporting to be used by end users too ($13.6 billion) and those of relational data warehouse management ($12.1 billion). Platforms capable of managing non-relational databases (34.0% CAGR) and those related to Artificial Intelligence (31.4% CAGR) are those growing very rapidly.
According to a 2018 IDC survey of over 2,200 managers and executives, Data Analytics ranked first among the technologies to be introduced in the company during the year or during the next two, while Big Data ranked third among the nine suggested technologies. For some time, in fact, companies have been investing in research with the aim of applying BDA and of obtaining a greater awareness of what occurs within the company, useful to react more quickly to internal and external events and to support decision making.
What is its relationship with Cloud Computing?
Cloud technology, according to IDC, is BDA-enabled, since it simplifies data collection and storage through scalable, flexible solutions, often lower than others from an investment point of view, even for small and medium enterprises. Public cloud, in fact, shows an investment growth in the period 2018-23 with a CAGR of more than 73%.
“Big Data technologies – says Giancarlo Vercellino, associate research director of IDC Italia – may be difficult to implement and manage in a traditional, on premise environment. Add to this the exponential growth of data and the complexity and cost of their management, and you can imagine the scale of the organizational challenge. However, the cloud can help overcome obstacles. When we look at the possible trends for BDA in the cloud, the three main areas which will benefit are those related to professional, personal and consumer and media services. In addition to these, BDA opportunities are also available to smaller and more innovative companies, which appreciate access to technologies previously considered unattainable due to cost or IT complexity“.
From Data to Artificial Intelligence
According to IDC, AI‘s worldwide spending on software platforms is expected to grow by 2023 with a compound annual growth rate of more than 35%; a tenfold increase of the market recorded in 2018. If you look at Italian data, over 30% of large companies are introducing applications using Machine Learning and AI.
The introduction of Artificial Intelligence systems, according to IDC, will slightly alleviate the workload carried out by professionals specialized in data management such as database administrators, data engineers, data scientists and BI developers, allowing companies to optimize their workforce and to make the development and distribution phases of new applications, products and services based on data more innovative.
All ready for data-based digital ecosystems?
“Big Data, Analytics and Cloud – answers Grazia Cazzin, director of Knowage Labs and the person responsible for the Engineering Big Data Competence Center offer – currently represent a combination of mutually enabling and qualifying technologies, architectures and systems. These are very closely related markets, whose combined growth proves the maturity not only of the BDA supply but also of the demand, now aware that what until a few years ago could have been an obstacle to the most innovative actions (lack of data, difficulties in supplying suitable machines, lack of skills), is now largely overcome.
The threshold for implementing Machine Learning and AI models has also been greatly lowered, thanks to the broad and widespread availability of open source resources and an open knowledge base. This, however, should not suggest that the market for ML and AI-based services can be reduced to an off-the-shelf offer. Both the application variety to inject intelligence into the new digital processes, and the quality of the results and the final usability in the everyday life of non-experts (which is where the expected return on investment is staked), depend greatly on the ability to deal with the many particularities of the individual contexts”.
