Getting a grip of your data is crucial to businesses of any size in this modern era. Having the proper systems in place is the best way to make sure that your databases, no matter how long you’ve had access, are able to be worked into insights for better business decisions today. This starts with having the right data virtualization software that integrates all of your datasets to make for an accessible and reliable source system for a proper understanding of your company’s needs.
Understanding Data Virtualization
Real-time access to the information that drives your business is crucial to getting ahead of the competition, and that starts with the right data virtualization technology. Data virtualization software acts as a bridge across multiple, diverse data sources, bringing critical decision-making data together in one virtual place to fuel analytics. This technology helps to form a modern data layer that enables users to access, combine, transform, and deliver datasets. It also provides business users with faster access to data housed throughout the enterprise, including their traditional databases and cloud-based systems.
With data virtualization, users can apply a range of analytics that helps to garner quicker access to real-time data and historical business data for deeper understanding. Through integrated governance and security, data virtualization users are assured their data is not only of the highest quality but also safe from unwarranted access. Virtualization technology allows for more business-friendly data, transforming native IT structures and syntax into easy-to-understand data services. This allows companies to find the data that they are looking for, free of replication and delay.
Use Cases of Data Virtualization Software
The use cases of data virtualization break down into three categories: analytics, operational, and emerging. Analytics use cases refer to the physical integration of data, creating a semantic layer for businesses through a logical data warehouse. Operational cases refer to an abstract data layer, also known as a virtual operational data store. This is more for registry-style data management operations. Emerging cases are linked to the cloud sharing of business data. This includes data hub enablement and content integration across all platforms.
The goal of all three is to maintain agile design and development to be able to introspect available data and discover hidden relationships within insights. The application of such software and source systems is highlighted by a high-performance runtime on any optimized query. This capability allows for real-time data and less replication of varied data sources. This includes the caching of essential data to boost performance and avoid network constraints. This affords business users 24/7 availability to a business directory that makes data with true business value easier to find.
Data Virtualization and the Business Community
The great thing about data virtualization software is that it can be used across a variety of industries. Take the energy industry, for example, which turns to data virtualization for improving maintenance and repair of their systems. Being alerted to an emergency in real time allows utilities to better address a performance issue and rectify situations quickly. Larger oil companies may rely on data virtualization technology to optimize their refinery processes or even analyze the performance of their offshore outlets.
The communications and technology realm can turn to data virtualization software to better handle their market research, while the health care system can use this software to better handle and pinpoint claims made under health insurance policies. There are no limits to the industries that can turn to dealing with a source system with real-time data. Data virtualization technology can be an asset for any program that relies on business intelligence to help them make the best decisions to better the company.