Laura DiDio, Director, IoT Strategies Service and author of the report, said corporations’ increased use of analytics – particularly in the healthcare, financial, industrial and manufacturing IoT vertical market segments, enables them to “interpret the vast amounts of data they generate and respond to market dynamics in ways that benefit the corporation and its customers.”
Big data analytics is the difference between being proactive and reactive, said Andrew Brown, Executive Director of the Enterprise and IoT Research. “Predictive analytics software can help businesses respond in a proactive way by dealing with issues before they occur while prescriptive analytics on data sources can suggest decision options that take advantage of the predictive elements and provide real differentiation and competitive advantage for companies leveraging these technologies."
Highlights include:
Highlights include:
IBM, SAS and SAP are the current and traditional market leaders but there are many powerful challengers including Bosch, Cisco, Dell, General Electric, Intel, Microsoft, and Oracle.
The big data analytics healthcare vertical segment will grow from US$7.964 billion in software revenue in 2015 to US$17.031 billion in 2022, a CAGR of 11% worldwide. The financial sector is the second largest vertical. Strategy Analytics forecasts that 2015 worldwide revenue will reach US$6.87 billion and will double to US$13.78 billion by 2022.
Much of big data analytics software will be open source, which is less expensive than proprietary software. It will also have the ability to run on commodity hardware, which OEM vendors are betting will help broaden its appeal to small and midsized enterprises.
The big data analytics healthcare vertical segment will grow from US$7.964 billion in software revenue in 2015 to US$17.031 billion in 2022, a CAGR of 11% worldwide. The financial sector is the second largest vertical. Strategy Analytics forecasts that 2015 worldwide revenue will reach US$6.87 billion and will double to US$13.78 billion by 2022.
Much of big data analytics software will be open source, which is less expensive than proprietary software. It will also have the ability to run on commodity hardware, which OEM vendors are betting will help broaden its appeal to small and midsized enterprises.
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