If your aging on-premises data systems cannot meet today’s demands for business agility and are time consuming and expensive to maintain, why continue to invest in them? Organizations looking to become more data-driven should consider accelerating their migration schedules from monolithic and siled systems that hamper innovation and agility to a modern data infrastructure.

The characteristics of a modern infrastructure are its flexibility and its ability to analyze and act continuously and automatically on holistic and current data. It allows you to store any amount of data at low cost in open and standards-based data formats. It is not limited by inaccessible data silos and allows users to perform analysis or machine learning using their preferred tool or technique. It also allows organizations to securely manage data access.

Running a legacy, on-premises or self-managed data infrastructure in the cloud, on the other hand, is time consuming and expensive. IT gets bogged down in worrying about installing and configuring hardware and software. Operations personnel must continually optimize data availability, performance, scalability, security, and compliance. Additionally, many on-premises data stores from commercial grade database vendors tend to be expensive and proprietary, and often involve vendor lock-in and punitive license terms.

Why the cloud does the trick

For these reasons, most digital transformation efforts involve migrating some or all of the company’s workloads to a public cloud platform. Instead of buying, owning, and maintaining data centers and physical servers, businesses can access computing resources, such as computer servers, storage, databases, analytics, and machine learning through Internet. The cloud provider handles all the mentioned management tasks, as well as software patches and data backups, thus reducing operating costs. The cloud also scales instantly, so you never have to worry about capacity planning and cluster scaling.

Additionally, thanks to AI and machine learning, cloud-based systems can process larger volumes of data to detect certain conditions and take automated action. These capabilities allow businesses to do business in new ways, minimize downtime and delays, and improve customer service and loyalty.

Samsung migrates 1.1 billion accounts from Oracle to AWS

Samsung Electronics, the world’s second-largest IT company, needed a more flexible, microservice-based database to replace its monolithic and expensive Oracle Internet data center solution. Expanding the existing system without downtime was risky and costly, and Samsung feared it might not be able to scale to accommodate the growing volume of users accessing its Samsung account certification and authorization service.

The company migrated a critical workload of 1.1 billion users from the account service to the Amazon Aurora cloud-based relational database service with minimal downtime in 18 months. In doing so, it reduced its monthly database costs by 44% while incorporating near-endless scalability. Samsung can also now serve more users faster: 90% of the latency in data access response times is less than 60 milliseconds.

Amazon Aurora is a MySQL and PostgreSQL compatible relational database designed for the cloud. Up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases, Amazon Aurora combines the performance and availability of traditional enterprise databases with the simplicity and cost effectiveness of open source databases. It is part of a broad portfolio of scalable, reliable, and secure AWS services and solutions that help organizations run their data and machine learning workloads at scale.

Reinvest your savings

Modern cloud infrastructures provide savings in the form of reduced software license fees, hardware and maintenance infrastructure, application development, and administrative overhead. These savings, in turn, can be reinvested in the growth of the business.

Once infrastructures are modernized, IT teams no longer have to waste time purchasing, configuring, testing, deploying and maintaining equipment and software. Instead, they can focus on using the latest advancements to create new services, enter new markets, and improve the customer experience in ways that increase revenue.

Learn more on how to reinvent your business with data.

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