How Data Virtualization Affect the Business Intelligence?

Data virtualization is any approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at source, or where it is physically located and can provide a single customer view (or single view of any other entity) of the overall data.

An increasing need for data virtualization solutions, automation, need to access large volumes of data stored across various systems to get a consolidated view, reducing infrastructure costs, increasing need to gain business insights, real-time availability of data, and an increasing demand for data integration software tools are some of the major growth drivers for the data virtualization Industry

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Data virtualization can be deemed to be an alternative to data warehousing and ETL.Unlike the traditional extract, transform, load ("ETL") process, the data remains in place, and real-time access is given to the source system for the data. This reduces the risk of data errors, of the workload moving data around that may never be used, and it does not attempt to impose a single data model on the data (an example of heterogeneous data is a federated database system). The technology also supports the writing of transaction data updates back to the source systems. To resolve differences in source and consumer formats and semantics, various abstraction and transformation techniques are used. This concept and software is a subset of data integration and is commonly used within business intelligence, service-oriented architecture data services, cloud computing, enterprise search, and master data management.

The major data virtualization vendors are International Business Machines Corporation (IBM; US), SAP SE (Germany), Informatica (US), Denodo Technologies (US), Oracle Corporation (US), TIBCO Software (US), Microsoft Corporation (US), Red Hat (US), SAS Institute (US), and Information Builders (US).

IBM is one of the leading vendors of the data virtualization solutions. The company follows inorganic growth strategy such as partnerships to enhance its products and solutions offerings in the data virtualization market. For instance, in March 2017, IBM formed a partnership with Salesforce to offer a solution by integrating capabilities of IBM Watson and Salesforce Einstein to help accelerate decision-making process by combining data from internal and external sources. IBM also launched a new product, IBM Spectrum Protect Plus, to help organizations meet requirements of real-time availability of data.

Another market-leading company, Denodo Technologies adopted the inorganic growth strategy such as partnerships to gain a dominant position in the data virtualization market. For instance, in February 2017, Denodo partnered with Semarchy to enhance its capabilities on various fronts such as marketing, sales, research, and partner development. Apart from that, expansion can be seen as a significant strategy that Denodo has been following. For instance, in August 2017, the company opened a new office in Singapore to cater to the growing demands for data virtualization technology in APAC.