Data Virtualization

Data is ubiquitous and the industry-leading organizations in the world are increasingly data-driven. Today Data flows in from disparate sources—such as databases, cloud/SaaS applications, Big Data, social media, XML, PDF, to name a few—before being processed and analyzed to enhance business processes and drive operations. However, here is a word of caution: cost, time, risk of error and complexity in gathering, storing, and analyzing such large and diverse data is ever increasing.

In addition, modern enterprises demand near real-time access to data notwithstanding the complexities and challenges involved in data movement and infrastructure requirements to store, process, transfer and protect this data.

Data virtualization addresses these challenges in data movement by ensuring that data remains at its source but, at the same time, is accessible in near real-time. Data virtualization can be used in business intelligence (BI), Big Data analytics, application development, and any downstream application, where it offers more agility, flexibility, versatility and cost-efficiency compared to traditional methods.

Data virtualization helps organizations gain easy access to data and overcome the delay in pulling in data from third-party sources, internal applications and databases, which could take weeks if not months.

How Intellium Can Help

Businesses that make full use of their data are the ones that are leaders in today’s business landscape.

Implementing data virtualization is more of a need than a choice for most organizations today, particularly those who rely on multiple data sources, who manage data in multiple locations, who want to reduce time-to-market for their products, who must improve risk management, and more.

Intellium Software provides the foundation for your organization’s data virtualization project, fulfilling your evolving needs with maturing architectures. We help eliminate data bottlenecks, enable consistency and reuse by delivering all data in a single logical layer that is curated, secure and serves diverse users.

We help businesses upgrade their technology ecosystem to improve efficiency and make the system more agile by migrating to the cloud. Indium helps organizations virtually integrate their varied data sources to enable users to build reports, perform analytics and manage other operational activities without any concern about the complexities.

We help build bespoke data models that meet client needs, while providing secure and selective access to your organization’s data powered by a single point of administration and control.

Our Partnership Overview

Intellium enables enterprises to successfully embark on their digital transformation journey through our collaboration with Denodo, thereby streamlining customer responsiveness across platforms and expediting time-to-market.
With our 20+ years of expertise managing data and Denodo’s 20+ years of expertise in data virtualization, we help businesses develop a smart, stable, scalable infrastructure for data management and governance.

With Data Virtualization, You Can:

Data virtualization’s consume layer provides single-point access and interaction for all the underlying data sources, while offering a wide range of data delivery options to meet different business user needs, through JDBC, ODBC, SOAP web services and more.

Data virtualization reduces the complexity with its unified data virtual layer from disparate sources and provides it to users virtually from a single source. This means organizations are not only able to integrate data with existing systems but can also minimize operational costs

Data virtualization helps standardize and uniformly deploy an organization-wide security and governance framework to adhere to General Data Protection Regulation (GDPR) laws. The application of these protocols on the virtual layer can help percolate the standards to the underlying data layer, ensuring coverage.

Data virtualization creates virtual views of the underlying data repositories, thereby eliminating issues pertaining to data replication, redundancy and consequently data synchronicity and quality.

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