Recent Accenture research shows analytics and data science have secured a spot on the boardroom’s agenda. That is because organizations are recognizing there are golden nuggets of actionable insights hidden inside the vast mounds of data – insights that will help them turn business issues into outcomes and advance on what Accenture calls the “Analytics Journey to ROI”. Analytics now plays an ever increasing role in various contexts such as broad as understanding what consumers are saying about you what may be a new product opportunity or business opportunity from monitoring social networks, to personalizing offers to customers in real time, making optimal pricing recommendations, preventing network failures, mitigating disease out-breaks, intelligent city planning and management. Big Data analytics focuses on letting data be industrialized in such a way that not only drives meaningful insights in a rapid fashion and also drives innovation for businesses and government.
Though the potential of analytics and Big Data is clear, one of the challenges noticed is a significant shortage of data scientists with deep analytical training in data discovery, predictive modeling, open source statistical solutions, visualization skills and business acumen to be able to frame and interpret analyses. Here, India is in an advantageous position. Over the last three decades, India has invested significantly in institutes and universities of national importance for higher education. All of these institutes have helped advance India’s talent leadership in the field of science, math, technology, operation research, management and fundamental research. India today has one of the largest pools of analytics and data science talent in the world and has been playing a key role in supporting the analytical needs of the developed markets. But make no mistake: With the rising adoption of analytics in business, even in India the most qualified analytics professionals, data scientists, are becoming a scarce resource.
Adoption of Big Data Analytics by Australian businesses and organisations is picking up momentum, with over 80% recently surveyed having already deployed or having plans to launch Big Data Analytics in the next 12 months.
A newly published survey of over 300 Australian organisations from all industry sectors by IDC, also found that about a third of them cited Big Data Analytics as “essential or critical” to their organisations.
According to IDC, the 80% rate of adoption or planned adoption, illustrates that Australian organisations are at different levels of maturity when it comes to Big Data projects, from ad-hoc and experimental discovery, to advanced analytical capability to drive decision making.
Airlines, hotels and reservation sites are making the most of data to improve booking ratios, boost revenue yield and improve customer satisfaction.
“We’re seeing tangible, pragmatic business benefits using big data, whether it’s to increase the look-to-book ratio, decrease the cost of operations, boost revenue yields or increase customer satisfaction,” says Herve Couturier, executive VP at reservation services giant Amadeus.
British Airways is doing more to remember personal preferences with its Know Me program, which goes beyond the loyalty programs based strictly on mileage rewards
It’s hard to imagine that something so small could create enough data to be used in research for big data analytics, but researchers at Toronto’s Hospital for Sick Children are using premature babies to do just that.
‘Big data analytics’ is the study of a large amount of data sets, broken down by computer systems that can detect trends. Researchers are collecting high-frequency physiological data, including heart rate and respiration rate, to create algorithms that can predict when a baby is at risk of infection and other health complications.
Premature babies, or preemies, demonstrate tell-tale signs of infection in changes in their heart rate up to 24 hours before an infection takes hold.
Once put in place, these algorithms can help doctors walk the thin line between life and death that preemies face.
Big Data’s going mainstream and at the same time it’s rewriting the rules of forestry management. Tree farmers, logging companies, plantations and conservation groups tasked with managing forestry assets can use Big Data analytics to dig up all kinds of insights that can help them achieve their goals of sustainability.
Predictive modeling is nothing new to the forestry industry. For years, its been used to forecast the impact of controlled burns, harvests and other forest management strategies. But until recently it’s been a slow and cumbersome process, involving thousands of man hours spent pouring over custom-made spreadsheets, with a whole lot of guesswork thrown in.
Forestry management presents an opportunity that’s capturing the attention of numerous Big Data companies, including giants like Google, organizations like NASA, and even a few plucky startups as well.