A database doesn't have to just be lists and lists of information. It can actually be the key to unlocking tons of insight to drive better business decisions. It's important for companies in this modern era to be able to format their data sources so that they can be turned into real-time analytics that drives up business value. The right data virtualization structure is the starting point to a bright future built on business intelligence.
What is data virtualization?
When it comes to better business processes, data virtualization solutions can take companies to the next level. Data virtualization software is a bridge across diverse data sources, bringing critical decision-making information together in one virtual place to fuel analytics. Virtualization provides a modern data layer that enables users to access, combine, and transform their datasets at breakthrough speed. Data virtualization technology gives users real-time access to information housed throughout their organization, from traditional databases to cloud systems.
With virtualization, users can apply a range of analytics on fresh, up-to-the-minute data updates. Through data integration and security, virtualization software users are assured their data is consistent and protected. Data virtualization allows for more business-friendly structures, transforming the usual syntax into something with greater visibility and understanding. This software supports multiple lines of business, hundreds of projects, and thousands of business users that can increase from one task to an enterprise scale.
What are the use cases of virtualization?
Data virtualization use cases expand into three categories: analytics, operational, and emerging. Analytics use cases center on physical data integration. This allows companies of any size to have easier data access through a semantic layer for analysis. A logical data warehouse may also be a case for this, making for better data preparation while limiting the risk of data errors thanks to regulatory constraints that have been placed on moving data.
Operational cases focus on an abstract data access layer, usually associated with registry-style master data management in a virtual operational data store. Companies often turn to data virtualization in these cases for legacy system migration and application data access. This also focuses on regulatory constraints on moving data. Emerging cases put a spotlight on faster access through cloud data sharing and access through internet-of-things (IoT) integration. IoT in these emerging cases allows for a connection through data hub enablement, along with content integration.
What sources can be a part of a virtual structure?
When dealing with any volume of data, proper virtualization solutions are necessary to afford a dashboard of all available data. Common data sources can be virtualized through this software, including packaged apps, along with XML docs and cloud data. Data warehouses and data lakes are more tangible than ever, preventing any past performance issues from disrupting further workload. With data virtualization software, common systems like Oracle and Google Big Query are brought into a scalable format that provides safe data storage that efforts better decisions for a business than traditional data integration and older methods.
Getting control of your organization's data is highly beneficial to accelerating business value, improving business insight, avoiding development costs, and reducing the cost of data management infrastructure. Various industry sectors can turn to these offerings from market research for a communications firm to driving production innovation in health care. Through correctly formatted data models, a data virtualization tool will emphasize real-time access in data services, making sure that an agile design and development provides the right structure for your business needs. If you're looking to give your company a competitive edge in a crowded marketplace, data virtualization software is a good choice to invest in for the long run.
