Magazine: A goldmine for companies

IBM’s estimation is that 2.5 exabytes (2.5×109 GB) of data are created in the world every day. About three quarters of this quantity are unstructured. What is big data? Experts define it as high-volume, high-velocity and high-variety information asset. There are four dimensions of big data (4V model): volume, variety, velocity and value – these characteristics describe big data the best. Special technological and analytical methods are needed to make big data valuable: the information extracted can be used very well in decision making. Péter Budai, the head of Microsoft Hungary’s server and cloud computing technologies division told our magazine: the fact that today basically all business processes – including production and sales – are supported with digital systems means that more and more data become available to companies. Those firms which are able to collect and process these acquire significant market advantage. Sanjay Gupta, director of business intelligence and information management solutions at T-Systems Hungary added that big data creates opportunities in data management which would seem impossible to have by using traditional data management techniques. A typical method of big data use among FMCG companies is sentiment analysis – examining what consumers think about a given product, campaign or brand. a perfect tool for such analysis is T-Systems Hungary’s Social Media Command Centre. Csaba Balázs, a product expert with SAP Hungary Kft. told Trade magazine that FMCG companies have to work with large volume of data and if these are rapidly converted into business information, better decisions can be made. Not only Lidl or eBay use big data tools, but also small businesses operating just a few stores. Attila Oláh, managing director of Esri Hungary revealed that in his view FMCG companies are sitting on a goldmine, but they only exploit a very small part of it. Lots of data remains unutilised and many of these are location-related; spatial analysis can help find the connection between such data sets. Attila Bódogh, managing director of Xdroid reckons that FMCG companies can profit from big data analysis, using data not only from production processes but also from the whole logistics and distribution chain if they enter into an agreement with retail partners. Relying on the iBeacon and RFID technologies and using the large databases of loyalty programmes, they can get great help in their innovation work, pricing, marketing and promotion campaigns. The most important thing is to start thinking in a data-centred manner. Small businesses can choose from numerous CRM software and business management systems to use for this purpose. Mr Budai is of the opinion that the best approach is to start with smaller, targeted business intelligence projects, for instance in the domain of sales. Sanjay Gupta’s advice to companies is to define precisely what kind business problem they wish to solve. The next step is to check whether data is available for solving these. If the answer is yes, an in-house, data warehouse-based reporting or information providing system is the solution. If there is no data available at company level, a data source needs to be found and it is probable that big data technology has to be used. Mr Balázs explained to us that business intelligence tools such as SAP Business One version for SAP HANA are capable of displaying information provided by big data technology. SAP develops lots of ready-made elements which companies can use in their own decision-support systems. However, it is best if off-the-shelf software are personalised. Mr Oláh added that they offer off-the-shelf solutions in the domain of big data, but they also have personalised and integrated systems – even provided in a subscription scheme. Mr Bódogh is of the opinion that big data doesn’t necessarily have to be an off-the-shelf solution. With the spreading of cloud computing new solutions have started to appear in the market. As long as there are several ways of collecting, processing and visualising data, converting these into a business asset always needs to be examined on a case by case basis, possibly relying on advice from business intelligence and artificial intelligence experts. György Körmendi, the managing director of Clementine Consulting agrees with this opinion, saying that off-the-shelf products aren’t typical big data solutions, only if they come with personalised service. Frequently users integrate a cloud-computing service into their own systems, behind which there is some kind of big data technology.