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Boost for predictive analytics application [ITWeb](ITWeb Via Acquire Media NewsEdge) Nowadays, companies must extract meaningful business value from vast amounts of data, says Merlin Knott of SAP Africa. The evolution of in-memory data capture and real-time availability has given enterprises tools that can graphically build accurate models in minutes and then run these models in continuous iteration against live data to make predictions with a significantly better accuracy. So says, Merlin Knott, director of business analytics at SAP Africa, who notes that convergence of new market forces such as big data, mobility and cloud computing have resulted in a host of new and powerful opportunities for the application of predictive analytics. "Being part of a Google society, one that demands: 'I want the answer now from an ever-present yet invisible source, there is an expectation for quick access to information', this is no different for predictions. Users want to be able to use a simple graphical interface to ask a number of questions that lead to information that they can use," explains Knott. He adds that nowadays companies must extract meaningful business value from vast amounts of data, whether it emanates from transactional data typically generated within the enterprise itself or from unstructured data created by external sources in the cloud and elsewhere such as social media networks. He adds that big data and cloud can be a hindrance if an organisation doesn't have the right technology and support from partners. Conversely, if big data and cloud are used to simplify the user experience and provide actionable insight in real-time, then they are important analytical technology tools. "Businesses can no longer focus solely on delivering the best product or service, why just meet customer demands when you can actually anticipate them?" asks Knott. "With the right technology tools, you can now identify new opportunities and provide targeted products and services to your customers to boost their efficiency and client retention," he explains. According to Knott, effectively leveraged predictive analytics allows businesses to significantly increase understanding of their customers' behaviour, improve response to clients, and deliver tangible business value which will ultimately drive up profitability. "The resulting insight allows businesses to uncover hidden customer, employee, vendor and partner trends, anticipate buying behaviour and then take proactive action, and the implications are huge," commented Knott He notes that the big challenge a business faces when using predictive analysis is the quality of data stored on the Internet. "Quality is the big challenge, not volume," he explains. He advises that a business should see how critical predictive analysis is to the core business when making a decision to outsource, but advises that the mix of the two is likely the best answer - in-house skills with support from outsourced specialisation. In conclusion, Knott explains that enterprises need to consider if they have the architecture to support real time predictive analytics and also take into account the high transaction volumes, customer numbers and the complexity of the competitive landscape. (c) 2014 ITWeb Limited. All rights reserved. Provided by Syndigate.info, an Albawaba.com company |