Journey to the Cloud with Analytics and Machine Learning

Executive summary

The ability to predict which strategies will succeed is critical to today’s organizations to scale new business models and pivot from potential failures while addressing current market demands responsively. For such predictive capabilities, businesses require the ability to deploy predictive models as analytics solutions. Also, ingesting and processing terabytes of data at high speed demands more advanced solutions than the on premise analytics solutions that organizations typically deploy.

The ideal solution is to leverage machine learning with analytics on the cloud. This combination provides extremely powerful data analytics to drive higher ROI. Machine learning and advanced algorithms are increasingly the norm today, and best-in-class analytics platform vendors provide solutions with predictive and cognitive capabilities.

What are the unique advantages of cloud platforms for big data analytics?

With cloud, collecting data from all internal applications, social networks, devices, and data subscriptions becomes much easier. Cloud analytics platforms support scale, deployment speed, agility, and rapid prototyping of analytics workflows to make on-premises analytics solutions passé. Big data platforms such as Hadoop, R, and Spark provide advanced workflow integration with cloud platforms to help you leverage the benefits of real-time and predictive analytics more efficiently and effectively. A services provider with deep competencies in cloud implementation and add on services for analytics can help enterprises realize full value from machine learning and analytics platforms on the cloud.

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