BIG DATA
Enterprise Data
Transactions
BIG Data
Social Media
Public Data
business model. “Data is very important for us,” says Michael Luplau, head of DC’s Analytic Team. “It’s one of the key foundations of our company and it’s getting increasingly important for being able to scale our business.” With an IT strategy that has a data branch and an intelligence branch, they are building an expandable data infrastructure and business intelligence team that drives their business now and in the future. Lawrence Austen, chief risk officer of commodity
Sensor Data
structured data volume seem like small change. In 1998, Merrill Lynch cited a rule of thumb that somewhere approaching 80-90% of all potentially usable business information may originate in unstructured form. Furthermore, Computer World states that unstructured information might account for more than 70–80% of all data in organisations. This ‘data within’ is, for most organisations today, an untapped resource. To make any sense of this data, technology is the answer, as it allows us to analyse these large data sets in near real-time to gain competitive advantage.
‘data within’ is, for most organisations today, an untapped resource
An example of this, by business author Bernard
Marr, highlights perfectly how this explosion of information, from a seemingly disconnected pool, can provide valuable nuggets of information that can be monetised. “Wal-Mart is able to take data from your past buying patterns, their internal stock information, your mobile phone location data, social media, as well as external weather information,” he states, “and analyse all of this in seconds, so it can send you a voucher for a BBQ cleaner to your phone – but only if you own a BBQ, the weather is nice and you currently are within a 3 miles radius of a Wal-Mart store that has the BBQ cleaner in stock.” An
example closer to home is Danske
Commodities. This asset-light company applies a new and refreshing business strategy – treat data as a strategic resource and invest heavily in technology to help achieve your goals. With a third of all staff engaged in IT and development, record profits of US$52.2m equivalent in 2012 and now operating in 32 countries, there is a high confidence in this
50 March 2014
trader Trafigura, said at a recent conference in London that, “Commodity trading firms stand to benefit from a crucial strategic advantage by grasping the opportunity presented by Big Data.” He added that, “In future, firms will need huge amounts of ‘high dimensional’ and ‘computationally intensive’ statistics to obtain the insight they require. This is what Big Data is all about.” Although this topic thread was one of many at
this particular conference, Big Data forums are now awash across the globe. It‘s a hot topic and an industry that is still in its infancy. Trafigura have spurned the traditional C/ETRM
system for an in-house one, which uses non- parametric statistics (high performance analytics) instead of the more established and traditional risk management methods. When you have firms managing portfolios of billions of dollars, even a modest improvement can translate into savings in the tens of millions of dollars. In fact, recent Cisco research estimates that
the ‘Internet of Everything’ (defined as bringing together people, process data and things to make networked connections more relevant and valuable than ever before) and the data it makes available, can unlock $19 trillion of value for companies worldwide over the next decade. It will do this by improving customer experience, innovation, supply chain, asset utilization and employee productivity.
Artificial Intelligence Meets Business Analytics In the software mainstream, Bloomberg and
Reuters now incorporate sentiment analysis services in their products, complete with visualisation capabilities. Reuters recently stated they want to “... turn qualitative, unstructured text into quantitative and actionable insight for our customers.” Sentiment analysis is certainly not new – it has been used for many years in government domains of defence, equities and the FMCG field with reasonable success. Broadly speaking, it analyses the comments from social networks and other mediums that identify the attitude, feeling or opinion towards a particular conversation thread on a product, company, brand, stock, commodity,
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