Big data leads to complicated and sometimes messy information, which is why according to worldwide research 85 percent of Fortune 500 businesses will not be able to use Big Data effectively (until 2015) to create a competitive advantage. Collecting data and analyzing it is not enough, as data streams are expected to also generate the right conclusions at the right time. The problem is that almost 80 percent of the data is often unstructured and polluted with useless data. However, some businesses have pioneered the use of Big Data and have thereby profited from it.

WalMart: diverse large suppliers are completely responsible for their own stock-management, informed by WalMart’s management system. This means they only sell their products once they are sold at the counter of WalMart. Walmart is thereby the leader in Commercial Big-Data applications.

Buzzcapture: The algorithms of this business sort online conversations about clients such as ING and Vodafone based on relevance, and can even estimate whether messages are angry or happy. It thereby often knows of disturbances before its clients do.

Erasmus MC: The Erasmus University Medical Center Rotterdam works with DNA sequencing techniques, which can provide almost one and a half terabytes of information about only one tumor. It has developed a data model which has significantly sped up the response time on gathering this information, which makes its cancer research much more efficient.

Cablecom: By analyzing the timing of the subscription cancellation of Cablecom (a telecommunications company), it has been able to reduce the number of cancellations in one year from 20 to 5 percent by offering clients a better deal when they might be contemplating canceling their subscription.

IBM: A selected group of drivers are testing IBM’s ‘Traffic Prediction Tool’, an app which uses GPS-data on the drivers’ driving habits, which can be personalized to give advice for the optimal route to their desired destination.

Rolls-Royce: this company has attached sensors to its engines which relay real-time performance data to its central database, thereby enabling the company to accurately predict when an engine needs repairs or maintenance.

Li&Fung: this Chinese supply-chain operator is one of the largest in the world, and their real-time processed transaction information means they are a very accurate estimator for economic development. Investment analysts gladly pay for this kind of information.

Equens: together with the Fraud Detection Expertise Center, Equens, a payment processor, has developed a system which analyzes transactions with lightning speed so as to detect the location of the skimming of bankcards, and also blocking these skimmed bankcards with immediate effect.

Capital One: This credit card company has developed algorithms which use a ‘predictive optimization engine’, based on previous website visits, which can estimate the social rank and income of a Capital One website visitor, thereby advertising only certain deals to them.

Visa: its use of novel and highly effective software has meant that it has been more efficient in managing its data streams, by decreasing the time taken to analyze all its transactions from one month to 13 minutes using the new Hadoop system from Apache.

Kaggle: a start-up which organizes competitions whereby participants must make extraordinary predictions by analyzing large data sets. This increases the incentive for companies to analyze their data more efficiently.

Nestlé: much of its data about clients, suppliers and resources was outdated, incomplete and even incorrect or duplicated. By using new information systems to clean up this mess it has saved an estimated total of one billion dollars per year.

Please let us know which company in your view is the smartest and why.