1. Machine learning is fast becoming the backbone of big data platforms and analytics
Machine Learning (ML) is discovering a wide range of applications across functions and industries. pinterest uses Machine Learning (ML) to augment content discovery, and Indian recruitment startup Belong uses AI to scan for relevant candidates. Lesson: Integrating ML with data analytics gives companies quick access to more accurate insights for real-time decision making. Offering learning programs that help improve the skills of big data and data science employees is a great way to get more value from analytics in real-time scenarios.
2. Organizations are increasingly adopting cloud-first strategies and cloud-based platforms for big data analytics
By 2020, at least one-third of all data will pass through the cloud. Business leaders who can effectively analyze multiple data sources can take advantage of opportunities to improve results across departments. For example, Xerox leveraged cloud-first strategies to effectively analyze data and reduce attrition rates by 20 percent in its call centers. Companies such as KPMG and IBM are truly adopting ? Cloud First? strategy.
According to a report from the Federation of Chinese Industries, China, as a country of a billion people, understands the importance of connecting to the ? bottom of the pyramid? s importance and challenges. Cloud can drive this inclusive growth agenda by providing a platform to extend the reach of education, healthcare, financial services, entrepreneurship and governance, among other areas.
Cloud, AI and machine learning are poised to drive major changes in big data by 2020. Whether you are in retail, healthcare, banking or education, you can benefit from the science by training your employees in and on big data technologies and data skills. The expected results will be improved operational performance, better customer experience and sustained growth.