Organizations in the 21st century are recognizing more than ever that having control of their data is crucial to making better business decisions. The ability to control these data sources is accomplished with a proper data management system, along with virtualization software that brings analytics and insights to life. TIBCO is one of the leading providers of these data virtualization tools, and here is just some of what their software can accomplish for business across various industries.
Agile Design and Development
Data virtualization provides a modern data layer that enables users to access, combine, transform, and deliver datasets with breakthrough speed and cost-effectiveness. Data virtualization software gives users real-time access to data housed throughout the enterprise at a fraction of physical warehousing and extract/transform/load (ETL) time and cost. This software acts as a bridge across multiple, diverse data sources to fuel analytics. Data virtualization is designed to transform business data across hundreds of projects and thousands of business users across a properly implemented source system.
Data virtualization software is able to introspect available data, discover hidden relationships, and modify as required. These capabilities automate difficult work and improve the time it takes for business users to achieve a solution. With these data platforms, proper formatting and data integration are key. Through integrated governance and security, virtualization users are assured that their data is consistent. This allows for more business-friendly operations to comb through technical details for simplified analytics and insights.
High-Performance Run Time
Data virtualization technology is designed to provide an easily accessible dashboard for business users to be able to access a virtual data pipeline. With the right data virtualization layer, the application invokes a request with the optimized query, then executes a single statement. This capability allows for up-to-the-minute data, optimized performance, and less replication. Within operational use cases, companies are able to migrate legacy systems of varied data sources, incorporating those offerings into a cloud-based service for quicker access.
Allowing for a more common approach from end-to-end, businesses avoid the risk of data errors that improve business value acceleration and insight improvement. With a faster run time to tackle these data sources, virtualization technology is providing an effective analytical outlet across different industries. For example, in the communications & technology sector, businesses are able to optimize customer care from this source data. With quicker virtual views and snapshots of data in real time, companies can differentiate their market research services and build a virtual customer data lake.
Making Queries Easier
With a large front of multiple data sources, virtualization tools afford greater use of business intelligence tools. This approach to data virtualization caches essential data. Through this method, the application invokes a request, and an optimized query is then executed to address business data. This capability boosts performance, avoids network constraints, and allows real-time availability. This virtualization capability includes features for search and data categorizations, browsing all available data while selecting from a directory of views to determine the best use of this information through the virtual layer afforded by this software.
With proper data storage, companies are able to make a good choice when it comes to decision-making, with easier access to the facts that will back up the decisions made. With the ability to comb through a data warehouse quicker, businesses in several realms are able to improve their workflow. In the health care sector, this is helping insurance companies address claims more quickly, while also forwarding product innovations based on the heterogeneous data provided through this system. Data virtualization software is a worthwhile investment and better for the sake of data governance and greater insight.
