Harnessing the power of cloud computing to enable smaller companies to use big data and grow their business is the focus of a new project.
Dr Giuliano Casale, from the Department of Computing at Imperial, is coordinating a new €4 million project, funded by the European Union, which will give small to medium sized businesses (SMEs) the ability to analyse and use large data sets or big data via cloud computing technology.
The advent of the internet and smart technologies such as mobile phones and tablets has meant that companies can collect masses of personalised data in real-time. Currently, only large multinationals have the financial and technical expertise to process this information, meaning that they have largely been the ones to financially benefit from this data revolution.
In the interview below, Dr Casale talks about how the new European project could level the playing field and enable SMEs to compete with multinational companies, which could ultimately enable SMEs in the UK and Europe to be more productive and prosperous.
What is cloud computing and how can it be used to help SMEs to harness big data?
Cloud computing allows businesses to rent out computing resources on-the-fly. For example, if I need a hundred machines to process my dataset, I can easily rent them from a cloud provider and pay only for the time I effectively use them, making it more cost effective for SMEs to use.
This means that SMEs can embark on big data projects, normally the domain of big business, where large datasets are stored and analysed directly in the cloud. All of this without the concern of building a private data centre, which is costly.
Why is accessing large amounts of data important for SMEs?
A concern of small and medium sized business is to level the competition with large companies. They are starting to see in big data a way to acquire business intelligence and compete more effectively on the market. Large datasets can reveal customer behaviours and these can drive the evolution of products or generate ideas for new services.
Can you give real-world examples of how SMEs could benefit from using big data?
Many SMEs are interested in using big data to personalise advertisement campaigns and to define loyalty programs based on the interests of their customers.
Other SMEs simply want to improve their products. For example, SMEs selling software to news operators are seeing social networks as a way to improve the coverage of breaking news. With big data technologies they can assess large volumes of social network data and extract in real-time useful information, such as images posted by eye witnesses.
Historically, big companies have been the only organisations to access and utilise big data. Why is this the case?
There are several factors. For example, big data require the adoption of many new technologies and developers with analytical skills. SMEs face major competition from large companies in attaining the necessary expertise from the job market.
Another issue is that big data projects are still seen as a risk. Some studies say that the percentage of big data projects that fail can be as large as 55 per cent. SMEs are therefore at a disadvantage compared to large organizations, since project failures can have more severe financial consequences on their business.
Imperial has been funded by the European Union to carry out a project to help SMEs access and use big data. Tell us more about it.
The project is called Developing Intensive Cloud Applications with Iterative quality Enhancements (DICE). The project focuses on helping SMEs create big data applications. The consortium is composed by nine European research organizations, including four academic institutions and five SMEs, and it is coordinated by Imperial. We are aiming to develop new ways to help independent software vendors accelerate the development of big data applications for SMEs.
What do you hope the ultimate outcome will be when the project is completed?
DICE will enhance the capability of SMEs to enter the big data market. The vision is to tackle skill shortages and steep learning curves of big data technologies through development tools that are highly automated. These tools will be easy to use and will simplify the task of building a big data application from scratch. We see this as a way to foster the adoption of big data technologies in SMEs. We are also trying to ensure that the methodology generates big data applications that are reliable, cost-efficient, and safe to use.
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