Modeling in SAP HANA Cloud

Opportunities for Innovation in the Digital World

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Discover the Opportunities Presented by Latest Technologies

Opportunities to Develop Modern Applications

Before we dive into the details, we should take a step back and look at the drivers that lead to SAP developing the SAP HANA Cloud service.

Let's look at some of the opportunities for the development of modern applications, in the new digital world.

Watch this video to learn about the new opportunities in a digital world.

New Opportunities in a Digital World

In our modern, digital world we are more connected than ever before, with staggering amounts of valuable data being generated every day by organizations and individuals. More and more services are moving online and new digital businesses are appearing. This trend is set to grow exponentially. Forward thinking organizations are already taking steps to adapt to the new, digital world and grow their businesses by exploiting new technologies.

The exponential growth of mobile devices, social media and the huge data volumes they generate has transformed the way we live and work. Most companies report that the majority of their people use mobile devices in their roles to handle everything from e-mail to project management to content creation.

But it is not just people who are connected. We are seeing a dramatic increase in the number of devices that have become "intelligent" by including CPUs and internet connectivity built right inside. We refer to this trend as the Internet of Things (IoT). Nowadays, it is not unusual for devices to be able to connect online to create intelligent and real-time responsive environments.

New types of data have become available. As well as the traditional, structured columns and rows that represent master data and transactions, we now have access to other types of data such as unstructured text data, spatial data and graph data. We can now develop applications that combine these data types to provide even more insight.

Cloud computing provides opportunities for organizations to develop new applications faster that ever before by deploying cloud platforms that provide instant development and run-time environment. Clouds support flexible scalability so you can start with small pilot applications and then scale them to reach a greater audience. Clouds provide organizations with huge amounts of computing power on a subscription basis, so they pay only for what they need. Organizations can easily mix technologies by combining different cloud services. This means they can use the best tooling and platforms for each application.

Until recently, data science was out of reach for most organizations who did not employ highly skilled personnel to work in this area. Today, data science is within the reach of business users who can use simple tools to develop powerful data models that reveal valuable insights into their vast amounts of data.

These are exciting times and there are unprecedented opportunities for all organizations to grow their businesses exploiting the latest technologies.

Challenges Faced by IT

Watch the following video to get an insight into some of these challenges.

Watch this video to learn about the challenges faced by IT.

Challenges Faced by IT

But for many organizations, taking advantage of these new opportunities using their current technology is very challenging.

Typical IT landscapes have developed over time into multiple complex arrangements of purchased, acquired with developed applications, powered by multiple platforms. These platforms can be based on incompatible hardware from different suppliers. This can mean different operating systems and different databases, and even different application development languages. To pull together, these different applications, organizations have created interfaces between systems. But these interfaces require constant maintenance as individual systems evolve. This in turn adds to the complexity.

Integrating mass data storage solutions into a landscape is a challenge because legacy applications were not designed to manage data stored in various online tiers of various temperatures. The applications simply expected the data to be off-loaded to archives and out of sight. They do not know how to access cloud data or data lakes.

Consumerization is driving expectations of what business IT should offer its users. As business users become familiar with smart, instant-response consumer apps in their private lives, they also demand real-time, innovative applications in their jobs. These applications are needed to enable deeper insight and provide high-value decision support to enable them to perform well in their business roles. Users also expect to be able to carry our their duties using a broad range of mobile devices so that they can react immediately to opportunities or risk, when away from their desks.

Organizations have developed applications that have been extended and modified over many years. These applications are increasingly difficult to enhance as the code becomes more complex. A business user asking for a small adjustment to an application, can be a major undertaking.

For many organization however, their current business systems cannot cope with the increasing demands of the highly connected digital world that is generating data at scales we have never seen before. We cannot just keep adding more complexity to existing IT landscapes in the hope that we can keep pace with trends. What is needed is a fresh start. It is time to start with a blank canvas and rebuild the business systems from the bottom up. This fresh start must be built on the latest technologies.

Data Silos

Silos of Data

One of the biggest issues with current IT landscapes is the inefficiency of the popular 'shift and lift data’ approach. In the past, it was necessary to periodically move data away from transactional applications into dedicated analytical systems. We did this so that data could be cleaned and harmonized with data from other sources using specialist applications. This approach also frees up the transactional system from the task of storing data used only for analysis. But as a result, multiple copies of the data are created in various places during the movement phase. But even worse, there is latency between the systems while the data transfer is pending. This means that we do not have a consistent picture of data across the enterprise at any moment.

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