Analytics market to keep growing with digital transformation

21Nov - by aiuniverse - 3 - In Human Intelligence Machine Learning

Source – cio.in

From enterprises to power stations, hospitals and public transportation, the volume of real-time data generated is unprecedented today. Data has become a crucial part of the smooth functioning of business operations and is unleashing new user experiences and an unseen world of business opportunities. With the generation of more and more data, the opportunity of analytics to derive profitable outcomes for businesses is growing rapidly.
In order to adapt to disruption and benefit from the digital transformation, organizations are leveraging analytics tools and taking a focused approach to developing the true value of information. In such a context of rapid transformation, data and analytics cannot be considered separate from each other.
The presence of large complex data sets is why technologies like deep learning and machine learning have risen to become one of the biggest trends in analytics, with large tech organizations are heavily indulging in open AI hardware and software.
Gold among heaps of data
The world data sphere will skyrocket to 163 zettabytes, ten times the 16.1ZB of data generated in 2016, says IDC. Corresponding to such humongous growth in data volume, data monetization is continuously becoming a major source of revenue, with analytics market expected to get a major surge in the coming times. Worldwide revenues for big data and business analytics will boost to more than USD 203 billion in 2020, at a compound annual growth rate (CAGR) of 11.7 percent, says IDC.
 
Challenges remain
As we move ahead, big data is still a challenge for businesses for the fact that analyzing massive, complex sets of constantly changing data remains a difficult task for businesses. Another is the analysis of unstructured data that remains a challenge. For data analytics to truly improve business efficiency in the coming years, IT professionals need to develop an end-to-end architecture so as to achieve the scale and agility necessary to analyze big data.
The rapid scalability of cloud computing makes this task possible. With increasing migration of operations to the cloud, along with readily available analytics tools, cloud vendors are giving a strong competition to traditional analytics organizations. IDC predicts that by 2018, new cloud pricing models for particular analytics workloads will push up to 5 times higher growth in spending on cloud versus on-premises analytics solutions.
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