As everything that people do goes online, businesses will continue to collect massive amount of data that has to be stored, managed, processed, and protected. Large volumes mean that sound database management becomes extremely important.
It is also safe to assume that as businesses grow and security concerns rise, the landscape of data storage and management is only going to get more complex, and issues like poor application performance and compliance risk will keep surfacing.
Oracle’s recently-launched Oracle Cloud integrates applied machine learning to deliver self-driving, self-tuning, self-recovering, self-scaling, and self-securing administration—without human intervention—resulting in streamlined operations, more efficient consumption of resources, and higher security and reliability. Let’s take a look at how this can potentially help businesses overcome several key database management challenges.
For modern businesses and organisations, the ability to react quickly to ever-changing business environment, trends, and technological forces is extremely essential. Maybe a decade ago, businesses had the luxury to take months or even years for their development cycles. But it isn’t so anymore. The elasticity of database management systems must cater to these needs.
The Oracle Autonomous Database is the world’s first fully automated cloud database platform powered by machine learning. And its computing and storage capacity are instantly elastic. It renders businesses the capability to scale up or down instantly, with no downtime.
Simply put, if you need more storage, you can scale up instantly; if you need less, you can scale them down, and then restart as and when there is demand for it.
A recent report by cyber risk management advisor Coalfire suggests that large enterprises are the least prepared of all companies against cyber crime, despite having greater budgets and resources. In general, the vulnerability of businesses to cyber attacks has increased manifold, and there are more sources that cyber threats emanate from.
Managing the security of databases, therefore, has become a huge challenge. Security operations centres are flooded with data and events, and they are constantly trying to correlate and distil large amounts of data to help identify potential risks. Today, technologies like artificial intelligence (AI) and machine learning algorithms assist security operations centres to manage configurations, and monitor who has access to what resources. These technologies are also helpful in encrypting data and protecting IT assets.
The Oracle Autonomous Database is more secure than a manually operated database, because it protects itself rather than having to wait for an available administrator. This applies to defences against both external and internal attacks.
It is capable of automatically encrypting all data to provide a secure configuration and prevent data access from outside the database. It applies security updates to protect against external attacks, automatically. The Oracle Autonomous Database is also capable of leveraging security technologies like the Oracle Database Vault (which separates duties to make sure data is not visible to the people who administer your systems) and Oracle Data Masking (which keeps developers and QA personnel from seeing your data).
One of the biggest advantages of the Oracle Autonomous Database is cost efficiency, as it reduces the amount of labour required and also cuts down on administrative costs. It can cut administration costs up to 80% with full automation of operations and tuning, and cut runtime costs up to 90% by billing only for resources needed at any given time. It can eliminate human labour to provision, secure, monitor, backup, recover, troubleshoot, and tune databases. All these put together can reduce database maintenance tasks, which in turn reduce costs.
Additionally, it is also easy for developers to use, and it will free up administrators form the mundane and tedious operational tasks, and they will actually have the opportunity to use their time better, and focus on innovation.
4.Tuning, Troubleshooting, and Patching
Databases used for mission-critical activities, or for enterprise data analysis, have a set of special challenges of their own. Databases that support enterprise data warehouses tend to become really big in size as they support complex queries with many nested joins. At the same time, they are expected to deliver quick response on the queries.
Database administrators are also in the constant process of trying various techniques to boost performance, creating and dropping indexes, changing data storage allocation parameters, and defining and redefining partitions. In addition, they are also monitoring the database for problems and performing preventative maintenance. Then there are the processes involved in applying software upgrades and patches, which are not just tedious, but also highly disruptive and take a significant amount of time
All these challenges can be dealt with by using the Oracle Autonomous Database. It incorporates machine learning and artificial intelligence to enhance performance tuning and prevent application outages. It can manage a wide variety of tasks that are usually handled by database administrators.
Finally, the fully automated database cloud service is self-tuning and preconfigured for automated patches and upgrades. This means that any possibility of manual errors is eliminated. For organizations looking for cloud database offerings, and a fully managed database service from a proven database vendor, Oracle’s Autonomous Database can be the answer.
The Oracle Autonomous Database Cloud is just one step on a multi-step journey. It allows businesses to simplify their IT infrastructure and minimize capital investments by utilizing Oracle Cloud services for data management, applications, and business intelligence. Find out more here.