Big Data remains in the very nascent stages of adoption, but the potential for it to create a new kind of information economy overnight is unparalleled, according to Actian's John Santafero.

"Data is the new oil," he told attendees at CeBit 2014.

Santafero said that 88 per cent of the world's data is not being used yet, and just 1 per cent of all companies have invested in data analytics to produce results.

The big change in data storage has come through Apache Hadoop. Instead of having to select what data your business needs, and discarding the rest due to storage concerns, enterprises can now store it all and search through the data at a later date, as needed.

This is particularly important as machine learning algorithms and information foraging platforms emerge.

Santafero said that 70 per cent of all Big Data projects around the world are still in the laboratory, and never make it into production because data scientists have failed to prove a business case.

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It doesn't help that there is an estimated 500,000 person data scientist shortage around the world, and the best and brightest are being scooped up by the major IT corporates, such as Facebook and Google.

Santafero is already talking about Big Data 2.0, that is, the development of platforms that combine other data platforms, such as those that combine data and those that analyse data - ensuring they work together properly.

"Big Data 2.0 is about creating transformational value - there are already new kinds of emerging data being used," he said.

The future is seeing trillions of datasets time stamped with GPS, RFID, and other sensors. Alongside this we are seeing greater proliferation of behavioural data, and collection of individual's user habits via mobile apps. He estimates that you can determine 10,000 customer attributes using these methods already - this will produce micro-segmentation marketing.

"This kind of data has never been available to us before in history," he said.

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These kinds of 'winning' analytics aren't just being used to make sales, they can also be preventative analytics, such as stopping something detrimental from happening, such as an addition to banks' fraud detection systems.

This transformation model doesn't just ensure a customer advantage, but helps companies maintain their existing advantages.

Six building blocks in bd2.0

1. Unified platforms will provide modular approaches covering the entire analytic process.

2. Analytic building blocks will provide accessibility for non-skilled and less skilled workers.

3. Service layers will abstract away the complexity of underlying infrastructure.

4. Combining non-relational and relational data enables a richer set of analytics

5. Moving processing to where the data lives operationalizes big data and push toward real time.

6. Cooperative processing delivers faster time to value and better price performance.

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