We now live in a world where a flood of customer data is all around us. Extracting meaning from that data deluge is a strategic imperative for business leaders. Global spending on 'big data' applications by organizations will exceed $31 billion in 2013, according to the latest market study by ABI Research.
The spending will grow at a CAGR of 29.6 percent over the next five years, reaching $114 billion in 2018. The latest ABI forecast includes the money spent on internal salaries, professional services, technology services, internal hardware, and internal software.
"We estimate that in big data initiatives salaries account for about half of the current spending, with the other half allocated to vendor products and services. What we're now seeing is quite significant overspending on salaries, as organizations turn to data scientists and other specialists in order to leverage big data in the first place," said Aapo Markkanen, Senior analyst at ABI Research.
Similarly, a good share of the money is spent on the associated professional services, for savvy and skilled analysts, which have sprung up to assist firms that are data-rich but skills-poor.
Narrowing the said skills gap, as well as improving the productivity of dedicated data scientists, represents a lucrative revenue opportunity for the sector’s vendors in the global marketplace.
Cloudera’s Impala project, the hitherto readiest attempt to enable SQL on Hadoop clusters, is an example of this demand being addressed on the database front. Going forward, ABI Research expects significant innovation, especially from the field of analytics.
Machine learning and its application in advanced analytics is one area that will make both the public and private sectors data-savvier than anything we’ve seen so far.
Traditional IT industry players are understandably moving in this direction, but at the same time we see analytics startups -- like Ayasdi and Skytree -- that have machine learning in their very DNA.
Eventually, such big data innovations will put analytics within any domain expert’s reach. At that point, data analysis and visualization will become more mainstream in all business circles.
The spending will grow at a CAGR of 29.6 percent over the next five years, reaching $114 billion in 2018. The latest ABI forecast includes the money spent on internal salaries, professional services, technology services, internal hardware, and internal software.
"We estimate that in big data initiatives salaries account for about half of the current spending, with the other half allocated to vendor products and services. What we're now seeing is quite significant overspending on salaries, as organizations turn to data scientists and other specialists in order to leverage big data in the first place," said Aapo Markkanen, Senior analyst at ABI Research.
Similarly, a good share of the money is spent on the associated professional services, for savvy and skilled analysts, which have sprung up to assist firms that are data-rich but skills-poor.
Narrowing the said skills gap, as well as improving the productivity of dedicated data scientists, represents a lucrative revenue opportunity for the sector’s vendors in the global marketplace.
Cloudera’s Impala project, the hitherto readiest attempt to enable SQL on Hadoop clusters, is an example of this demand being addressed on the database front. Going forward, ABI Research expects significant innovation, especially from the field of analytics.
Machine learning and its application in advanced analytics is one area that will make both the public and private sectors data-savvier than anything we’ve seen so far.
Traditional IT industry players are understandably moving in this direction, but at the same time we see analytics startups -- like Ayasdi and Skytree -- that have machine learning in their very DNA.
Eventually, such big data innovations will put analytics within any domain expert’s reach. At that point, data analysis and visualization will become more mainstream in all business circles.