If your aging on-premises data systems are unable to meet current demands for business agility and are time-consuming and expensive to manage, why continue to invest in them? Organizations looking to become more data-driven should consider accelerating their timetables for migrating away from monolithic, siloed systems that inhibit innovation and agility to a modern data infrastructure.
The hallmarks of a modern infrastructure are its flexibility and ability to continually and automatically analyze and act on holistic, current data. It lets you store any amount of data at a low cost in open, standards-based data formats. It isn’t restricted by inaccessible data silos and empowers people to run analytics or machine learning using their preferred tool or technique. It also lets organizations securely manage access to the data.
Running legacy data infrastructure on-premises or self-managed in the cloud, by contrast, is time-consuming and expensive. IT is bogged down worrying about hardware and software installation and configuration. Operations staff must continually optimize data availability, performance, scalability, security, and compliance. In addition, many on-premises data stores from commercial-grade database providers tend to be expensive and proprietary, and they often involve vendor lock-in and punitive licensing terms.
Why the cloud fits the bill
For these reasons, most digital transformation efforts involve migrating some or all enterprise workloads to a public cloud platform. Instead of buying, owning, and maintaining physical data centers and servers, organizations can access IT resources, like computer servers, storage, databases, analytics, and machine learning over the Internet. The cloud provider handles all the management tasks mentioned plus software patching and data backups, lowering operational costs. The cloud also scales instantly, so you never have to worry about capacity planning and cluster scaling.
In addition, thanks to AI and machine learning, cloud-based systems can process greater volumes of data to detect certain conditions and take automated actions. These capabilities enable enterprises to conduct 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, microservices-driven database to replace its monolithic and expensive Oracle Internet data center solution. Expanding the legacy system without downtime was risky and costly, and Samsung was concerned that it couldn’t scale to accommodate the growing volume of users accessing its Samsung Account certification and authorization service.
The company migrated a mission-critical workload of 1.1 billion Account service users to the Amazon Aurora cloud-based relational database service with minimal service disruption in 18 months. In doing so, it reduced its monthly database costs by 44% while building in near-infinite scalability. Samsung can also now serve more users more quickly: 90% of latency in data access response times is less than 60 milliseconds.
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built 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, trusted, and secure AWS services and solutions that help organizations run their data and machine learning workloads at scale.
Reinvest your savings
Modern cloud infrastructures deliver cost savings in the form of reduced software licensing fees, hardware infrastructure and maintenance costs, application development, and administrative overhead. Such savings, in turn, can be reinvested in company growth.
Once infrastructures have been modernized, IT teams no longer have to spend time procuring, configuring, testing, deploying, and maintaining equipment and software. Instead, they can focus on using the latest advances to create new services, enter new markets, and improve customer experiences in ways that help grow revenue.
Learn more about ways to reinvent your business with data.