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Experts at SAP Predict the Hottest Trends for 2019


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Another year is just around the bend and there’s already talk about the next big thing on the horizon. Experts at SAP are weighing in on what 2019 has in store, with trends spanning cloud, AI, data management, and more.

Philip On, global vice president of data management, SAP, believes 2019 will lead to the democratization of in-memory computing.

SAP pioneered the in-memory database almost a decade ago with SAP HANA, On said. Since then, many industry players have attempted to replicate the path that SAP HANA has set out for customers through powerful real-time data management and analytics.

“In 2019, SAP will make it a priority to bring in-memory computing to the masses by further raising the bar around openness, flexibility and security,” On said. “Expect to see powerful innovations surrounding new cloud and hybrid solutions, data pipelining, expanded data tiering options, and much more. These will be accompanied by expanded partnerships focused on further reducing the cost of in-memory computing implementations.”

In the coming year, 5G speeds will take data volume to new heights, predicts Ken Tsai, global vp, head of cloud platform & data management, SAP.

“In 2019, we can only expect the volume of data to increase exponentially (Gartner predicts the number of connected devices to grow from 23 billion to 31 billion by 2020) as IoT devices continue to become more commonplace and data can be consumed and computed at much faster speeds thanks to the rollout of 5G across the globe,” Tsai said. “As availability of 5G become widespread, this would lead to even higher volume of data being shared, we have an opportunity to evolve our current single cloud provider,  cloud native data computing architecture into something that is more peer to peer based, taking advantage of 5G speed.”

Tsai also predicts 2019 will be the year of the hybrid cloud. Companies are getting smarter about going to the cloud, and only transitioning where it makes the most sense for business growth and improving the customer experience. This is forcing cloud providers to evolve and fine tune their offerings, he said.

“We will see the cloud providers roll out new private cloud offerings that will more easily integrate with companies on-premise systems to create a customized or tailored hybrid network architecture,” Tsai said.” In fact, many large enterprises have already implemented their own private company clouds. In the coming year, we can anticipate seeing more integrated hybrid on-premise and cloud (public and private) architectures to increase flexibility, openness, security and scalability.”

In the year ahead, AI will be more than just a buzzword, especially in relation to business applications, said Dan Lahl, VP of product, SAP.

“PaaS will help developers combine conversational AI and semantic business knowledge to complete end-to-end business tasks,” Lahl said. “For example, a business can build a chatbot that users can communicate with in natural language, which then uses RPA to automate tasks by removing repetitive data entry and sending data to computer systems. Growing adoption of these new technologies will help significantly reduce technical debt and provide intelligent automation within the enterprise.”

He also expects to see consolidation among PaaS, CaaS and FaaS offerings as developers look to future proof their applications, and vendors focus on increasing automation and simplified orchestration.

“Kubernetes, containers, functions, etc. all provide significant value, but they can be difficult to use,” Lahl said. “Due to the rapid pace of innovation and increasing technical depth, there’s high demand for a seamless orchestration of tools that can accelerate the process for updating existing or building new applications.”

With a lack of data scientists, Mike Flannagan, senior vice president, Leonardo and Analytics, SAP, predicts enterprises will adopt self-service analytics tools in 2019.

“Those tools will empower the average business user to achieve some of the same insights for straightforward projects that would otherwise require skilled data scientists, freeing those data scientists to focus their expertise on more complex projects,” Flannagan said. “This will enable business decisions to be made faster than ever before.”


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