Major initiatives that I’ve seen heavily revolve around the utilization of data and the best possible ways to process it. This is why so many designs are now involving smarter and even automated data warehousing solutions. Let me give you an example. Let’s say you’re an Oracle shop that leverages an Oracle backend to do a lot of data processing. Well, now that both cloud and automation are on the table, how do you design around it?
Removing legacy data management components can be scary, costly, and time-consuming. However, new solutions are specifically designed to make all of this easier. Using the above scenario, many Oracle customers are now looking at new Oracle architectures to support evolving data requirements. Specifically, Oracle’s Autonomous Data Warehouse is designed from its core to be an easy-to-use, fully autonomous database that scales elastically, delivers fast query performance and requires no database administration. But here’s why this solution is so special. Built-in machine learning technology eliminates manual configuration errors to ensure reliability. In addition, unlimited concurrent access combined with advanced clustering technology enable businesses to grow data stores without any downtime. When it comes to cost and pricing, Oracle customers have fine-grained control of pre-configured compute and storage resources allowing for independent scaleup and down to avoid overpaying for expensive, unused, fixed blocks of cloud resources.
Pretty cool, right? Taking a step back here, you as an organization now have amazing options to work with vast sets of data. And, not just how you process and ingest all of it, but in the ways you’re managing your data sets as well. What Oracle is doing here is really special. They’ve basically designed the world’s first self-driving database cloud that’s architected to perform all routine database maintenance tasks such as patch, update, backup, without human intervention, all while the database is running. Coupled with machine learning, database migration tools, and enterprise-grade security, this type of autonomous data warehousing creates the foundation for the sustainable management of large amounts of data.
Here’s the really cool part. You can start taking all of this into the cloud. When it comes to cloud-based data loading, you can already integrate with fast, scalable data-loading from Oracle Object Store, AWS S3, or even on-premises. This means your cloud design can focus on the best possible use-cases around data management. Most of all, you can design around public, private, hybrid, and even multi-cloud architectures.
The scariest part is dealing with all of the data. But, none of this has to turn into a nightmare. The most successful data warehousing, and even cloud-driven data migration, projects that I’ve been a part of involve a holistic approach to data management. First of all, make sure there’s a good use-case. Then, it’s critical to involve all necessary stakeholders to ensure your project can scale. Finally, work with a good partner that can help navigate data design and cloud integration. Remember, leaders in the space are actively leveraging advanced data-driven solutions to impact the industry, their customers, and their competitive stance in the market. A great way to do this is to capture the value of data, and leverage the power of cloud and automation to make it all happen.