What is digital transformation? | Digital business transformation defined | SAP Insights

Digital transformation is underpinned by some of these core and new technologies:

Modern ERP and database technologies

The best cloud ERP solutions use in-memory database technology, making them highly scalable and adaptable. This is important because they are essentially the “brains” behind digital business transformation. ERP takes all the core processes needed to run a company (such as finance, HR, manufacturing, and supply chain) and integrates them into a single system. And when a modern ERP is powered by AI technologies, it has the power to not only manage and process Big Data, but to analyze and learn from it.

Advanced analytics

In order to deliver value, data needs to be harnessed and understood. Using AI and machine learning algorithms, advanced analytics provides insights and reports that are deep, accurate, and actionable. Businesses can also customize data analysis configurations on demand. This gives business leaders the power to act quickly and decisively – by seizing an opportunity or responding to risk.

Cloud connectivity

Cloud-based infrastructure is an essential component to successful digital transformation and the establishment of IoT networks and connected business systems. On-demand, centralized access to all systems, assets, and data allows organizations to scale infrastructure as needed and rapidly change or automate workflows. This helps to support rapidly changing business priorities and operational models. And as Forrester tells us, as of 2021, almost 60% of enterprises in North America rely on cloud platforms, which is five times the percentage it was just five years ago.

AI and machine learning solutions

Big Data grew up alongside AI and machine learning. In order to process and make sense of Big Data, it’s necessary to have the power of AI and machine learning. For AI and machine learning to deliver accurate and meaningful results, both must have large enough data sets to support robust learning and analysis. The partnership of Big Data, AI, and analytics is at the core of business and digital transformation – driving predictive planning and responsive automation.

Internet of Things

Devices and machines in an IoT network can send and receive digital data. Machine logs and maintenance reports are analyzed to optimize performance and efficiency. AI-powered business systems continuously analyze this information for patterns, trends, and correlations. These insights help drive predictive maintenance and automated workflows, increasing efficiency and productivity over time as the machine learning applications “learn” from the IoT data.

Robotics and robotic process automation (RPA)

Both robotics and RPA use automated processes to accomplish repetitive or pre-programmed tasks. Robotic devices are comprised of moving, mechanical parts set to execute specific, physical tasks. RPA processes are similarly programmed and automated – however, they exist as software processes rather than physical devices, and the tasks they perform are administrative in nature.