Cloud databases can help clear up the bottlenecks arising in today’s data environments in these ways:
Relieve overloaded infrastructures:
In many advanced data organizations over the years, decision makers turned to enterprise data warehouses to help capture, archive, organize, sift through, and make sense of their data. Data warehouses were revolutionary in their time because they cut across the many data silos that had sprung up in enterprises, providing data independent of specific applications or platforms. However, the deluge of data in varying formats—particularly unstructured data—and the need for real-time streams places strain on existing infrastructure, particularly data warehouses which may not have been built for unstructured data and real-time analysis.
Get more out of tight budgets:
IT leaders increasingly find themselves in a double bind. They need to address demands for increased access and capabilities, while simultaneously keeping a lid on cost. Cloud computing—particularly cloud-based databases or databases that support cloud—offers ways to address these challenges.
Cloud is inherently built on shared resources, and thus the costs are spread either across business units (within private clouds) or across customer bases (within public clouds).
Achieve greater flexibility:
Today’s data environments need extraordinary work. Plus, new clients and projects can be quickly put in place without a significant performance hit to existing data environments. Cloud databases can also be supported in a more automated fashion, reducing errors and providing for more end user self-service. If the business case is still uncertain or undetermined for a particular analytics application, deploying and piloting the application can be accomplished very quickly at minimal cost, without the need to borrow cycles from existing machines within the organization.
Enable greater innovation and speed:
With a pre-built, pre-configured cloud database solution available—either within the enterprise or supplied by an outside cloud vendor— new applications and systems can be stood up with a minimum of pre-design or integration work on the part of IT or data management staffs. IT and data management departments can focus on delivering analytics and other solutions without the need for long-term database modeling or development work. Plus, new clients and projects can be quickly put in place without a significant performance hit to existing data environments. Cloud databases can also be supported in a more automated fashion, reducing errors and providing for more end-user self-service. If the business case is still uncertain or undetermined for a particular analytics application, deploying and piloting the application can be accomplished very quickly at minimal cost, without the need to borrow cycles from existing machines within the organization.
Provide or compensate for needed skills:
Managing data in different formats from a variety of data sources requires the ability to bring this data together and integrate it into a common format. This requires professionals who are well-versed in extract, transform, and load (ETL) skills. The availability of cloud databases means that much of the underlying “plumbing” work of capturing and rationalizing data has already been addressed by the cloud provider, or within the shared enterprise environment—so IT staff can focus on analytics projects, versus reinventing the wheel with data standards.
Measure services:
Data services will generate significant amounts of data themselves, providing IT managers and administrators insights into service performance, uptime, and usage patterns.
Consolidate and standardize data environments and workloads:
Transforming database functions into cloud-based data services enables enterprises to take advantage of shared and highly scalable resources. Rather than be duplicated across business units, enterprise users have access to a single environment. The move to cloud, whether based on a private cloud platform or from a cloud provider, also means adoption of more common standards used by most new-age applications, services, and interfaces. Thus, new functions can be brought up quicker and easier than with the siloed database access points of the past.
In recent times, there has been a relentless demand for more capacity, more real-time insights, and more ability to support new types of data flowing into enterprises. Cloud databases address the needs of a more agile and data-driven enterprise, offering manageable costs, greater simplicity, more scalability, and enhanced flexibility. Much of the data now coming in, due to cost or structure, may even be better suited for storage within cloud-based environments as the first option. Cloud databases—either run directly from the cloud or supporting the cloud—have become a worthwhile option for many enterprises.