How to Start Small and Grow Big with Data Virtualization

Neha Gurudatt | June 9, 2022 | 836 views | Read Time : 02:10 min

datavirtualizationblog

Why Should Companies Care about Data Virtualization?

Data is everywhere. With each passing day, companies generate more data than ever before, and what exactly can they do with all this data? Is it just a matter of storing it? Or should they manage and integrate their data from the various sources? How can they store, manage, integrate and utilize their data to gain information that is of critical value to their business?

As they say, knowledge is power, but knowledge without action is useless. This is where the Denodo Platform comes in. The Denodo Platform gives companies the flexibility to evolve their data strategies, migrate to the cloud, or logically unify their data warehouses and data lakes, without affecting business. This powerful platform offers a variety of subscription options that can benefit companies immensely.

For example, companies often start out with individual projects using a Denodo Professional subscription, but in a short period of time they end up adding more and more data sources and move on to other Denodo subscriptions such as Denodo Enterprise or Denodo Enterprise Plus. The upgrade process is very easy to establish; in fact, it can be done in less than a day once the cloud marketplace is chosen (Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP). In as little as six weeks companies can realize real business benefits from managing and utilizing their data effectively.


A Bridging Layer

Data virtualization has been around for quite some time now. Denodo’s founders, Angel Viña and Alberto Pan, have been involved in data virtualization from as far back as the 1990’s. If you’re not familiar with data virtualization, here is a quick summary.

Data virtualization is the cornerstone to a logical data architecture, whether it be a logical data warehouse, logical data fabric, data mesh, or even a data hub. All of these architectures are best served by our principals Combine (bring together all your data sources), Connect (into a logical single view) and Consume (through standard connectors to your favorite BI/data science tools or through our easy-to-use robust API’s).

Data virtualization is the bridge that joins multiple data sources to fuel analytics. It is also the logical data layer that effectively integrates data silos across disparate systems, manages unified data for centralized security, and delivers it to business users in real time.


Economic Benefits in Less Than 6 weeks with Data Virtualization? 

In a short duration, how can companies benefit from choosing data virtualization as a data management solution?

To answer this question, below are some very interesting KPI’s discussed in the recently released Forrester study on the Total Economic Impact of Data Virtualization. For example, companies that have implemented data virtualization have seen an 83% increase in business user productivity.

Mainly this is due to the business-centric way a data virtualization platform is delivered. When you implement data virtualization, you provide business users with an easy to access democratized interface to their data needs.

The second KPI to note is a 67% reduction in development resources. With data virtualization, you connect to the data, you do not copy it. This means once it is set up, there is a significant reduction in the need for data integration engineers, as data remains in the source location and is not copied around the enterprise.

Finally, companies are reporting a 65% improvement in data access speeds above and beyond more traditional approaches such as extract, transform, and load (ETL) processes.


A Modern Solution for an Age-Old Problem

To understand how data virtualization can help elevate projects to an enterprise level, we can share a few use cases in which companies have leveraged data virtualization to solve their business problems across several different industries.

For example, in finance and banking we often see use cases in which data virtualization can be used as a unifying platform to help improve compliance and reporting. In retail, we see use cases including predictive analytics in supply chains as well as next and best actions from a unified view of the customer. There are many uses for data virtualization in a wider variety of situations, such as in healthcare and government agencies. Companies use the Denodo Platform to help data scientists understand key trends and activities, both sociologically as well as economically.

In a nutshell, if data exists in more than one source, then the Denodo Platform acts as the unifying platform that connects, combines and allows users to consume the data in a timely, cost-effective manner.

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