Global conglomerate General Electric (GE) has issued a reminder to organisations that customer trends is merely one facet of big data – there are also vast opportunities for insight from industrial metrics which should not be overlooked.
The US-headquartered company, active in a range of markets including energy, industrial equipment and finance with total annual revenues of $147bn (£93bn), has released a short white paper entitled ‘The Rise of Industrial Big Data - Leveraging large time-series data sets to drive innovation, competitiveness and growth—capitalizing on the big data opportunity’.
In it, the company quotes analyst firm McKinsey when pointing out that despite social media data taking the limelight in the early days of the rise of big data, “manufacturing stores more data than any other sector — close to two exabytes [two billion gigabytes] of new data stored in 2010”.
GE uses a consumer packaged goods company as a case in point. The unnamed personal goods product maker generates 5,000 data samples every 33 milliseconds according to the report, which equates to 13 billion samples per day (see graphic above). Before, much of this data would remain unexploited but thanks to the development of big data tools, with the drive accredited to Google, Yahoo! And Facebook in the report – it can now be used for actionable insight.
One example of this is the opportunity to understand the significance of temperature variation on quality as the speed of materials varies through a production line. Another is the ability to analyse of five years’ worth of past data for examining anomalies and variations to understand whether they were followed by subsequent outages to enable predictive analysis.
Big data tools and techniques also offer the opportunity to work with the data much more efficiently, the reports states. One example of this is that some programmes can “lean out non-value added data points” which makes the data much easier and cheaper to store, access and analyse.
The paper also includes a case study on GE’s own energy business and how it used big data to increase its storage capacity form three months’ worth of data to ten years’ worth and reduced its analysis time from “days or weeks” to “near real time”.
The report concludes: “Business and IT leaders need to ask themselves whether their industrial enterprise is maximizing the full potential value of their process data and using that insight to drive real-time improvements. As data volumes continue to expand, information-driven strategies will only become more pervasive as a source of competitiveness—making the use of big data in the industrial space ever more imperative.”