What is an example of data virtualization?

Virtualization data helps integrate virtual data management to enable applications to retrieve and process data without the need for technical details about the data, such as how it is formatted in sources or where it is actually located, enabling it to provide one for the total data.


Data Virtualization


Data virtualization is an aggregate term used in a data management approach that allows applications to retrieve data and manipulate data. The goal of data virtualization is to perform distributed data management processing, primarily for a query, against many heterogeneous data sources, and to aggregate the results of queries into a virtual view. This is followed by the consumption of virtual views in applications, reporting query tools, middleware, or other elements of the data management infrastructure.


Data virtualization can be used to create virtual, integrated views of data in memory, without relying on data transmission and storing the integrated views in a target data structure. This provides a layer of abstraction over the physical use of the data, in order to simplify the query process.


data virtualization


what is an example of data virtualization?


Data virtualization is a logical data layer that integrates all isolated enterprise data across different systems, manages unified data for central security and governance, and delivers it to business users in real-time.


Real-time delivery


Data virtualization provides integrated, real-time information for applications used by business users.


data management


Data virtualization provides a secure central layer for indexing, searching, discovering, and managing federated data.


data integration


Data virtualization integrates siloed data across all enterprise systems, regardless of data format, location, or latency.


Logical data layer


Data virtualization provides a virtualized way to access, manage, and deliver data without duplicating it in a physical repository.


data virtualization tools


Data Virtualization tools simplify and speed up access to data stored in data warehouses, databases, and files on-premises and in the cloud. By linking multiple data sources and centralizing data acquisition logic in a metadata layer, these tools create a single data source for data consumers. The tools support real-time and historical data. It is compatible with a wide range of formats and interfaces and facilitates data modifications.


Denodo


Denodo is a major figure among service providers with more than 20 years in the market. The latest version is equipped with a data catalog feature that makes it easy to search and discover data. The solution can be deployed in the cloud, on-premises, and in hybrid environments.


Who may benefit from using the tool: Denodo is well suited for small and large businesses that not only want to integrate their data through virtualization but also to understand their data and how it is used.


TIBCO


TIBCO Data Virtualization is another powerful tool on the list to help you build a virtual data layer from multiple types of data sources. To join data together from non-relational databases and other unstructured sources, TIBCO has an internal conversion engine that does all the jobs.


Who might benefit from using the tool: Companies that want a quick and easy implementation of a data virtualization strategy.


Informatica


As one of the leading data integration platforms, Informatica has many powerful features for virtualizing data. The basic element of the platform is a metadata manager equipped with a convenient visual editor that helps to see the integrations by mapping the flow of data across the environment.


Who might benefit from using the tool: This data virtualization tool is useful for organizations looking for a code-free environment with an intuitive graphical user interface for integrating diverse data sets.


IBM Cloud Pak for Data


IBM Cloud Pak for Data, known as IBM Cloud Private for Data until 2018, is a cloud-native platform that makes it possible to build a data fabric that connects orphaned data by default. In addition to data integration, the tool allows all users to control and analyze data from a single drag-and-drop interface. IBM also provides an enterprise-wide data catalog for more effective data discovery and organization.


Who might benefit from using the tool: IBM Cloud Pak for Data is a good choice for those looking for a focused solution packed with data collection and analysis capabilities.


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