Home » Data Virtualization: A smart approach to bringing BSS data silos together 

Data Virtualization: A smart approach to bringing BSS data silos together 

by Nathan Zachary

Data Virtualization: A smart approach to bringing BSS data silos together 

[Summary: Data virtualization let companies access data from a pool of data sources, such as- data warehouses, data lakes, and NoSQL databases-through a single window. This manages/governs the BSS data silos through a virtual layer that guards the original data source. But without any trade-offs.] 

“Starter kit” 

As per a recent report, the global data virtualization market is to grow at a CAGR (i.e., compound annual growth rate) of 20-6%. The market was $2.45 billion in 2019 & will hit $10.87 billion in 2027. 

The fact that data virtualization is a great way to manage data lying in the BSS domain as well is true. 

A huge amount of data is generated every minute. Processes like digitization, IoT, innumerable devices connected over the internet, & network advancements are the main reasons behind it. Further, cloud services, SaaS, and 5G network slicing are contributing to this data storm. 

What is Data Virtualization And How Does It Actually Work? 

Data virtualization is a process of storing data in one place and making it accessible from another. It is a way to centralize data with no need to duplicate it. Data virtualization provides the benefits of centralizing data, without the flaws that come with it. 

  • Let’s say you entered a query. The data virtualization layer will collect the optimal data from data sources, transform it further & deliver it. This can eliminate data barriers by providing easy & secure access to all data. 
  • Data Virtualization can be used for any type of database system, including relational databases, object-oriented databases, and even NoSQL databases. 
  • A CSP might have many BSS data repositories. Data virtualization helps in building a simple, unified, & integrated one-stop view without creating another data repository. This will accelerate many use cases in BSS.  

Virtualizing in the Trends in Big Data Management 

Big data management has become a necessity for businesses. Companies need to understand the trends in big data management- which will be virtualized and automated, in future. 

  • This will have more control over their data sources, thin middleware (of data virtualization), and data consumers. Providing quick & better insights for their business. 
  • Data virtualization is location-independent & enables CSPs to utilise data more effectively. In a faster & profitable manner! Above all, data virtualization doesn’t expose the true location or access protocol to the data consumer. 

How Data Virtualization helps BSS Data Silos? 

  • Agility: The legacy data integration system cannot keep up with the developing enterprises. Increased agility is demanded. And the traditional design (which is database-centric) further makes it dormant.  

The architectures are mainly based on a chain of data stores- which risk the on-time results delivery. 

Agile data virtualization is the answer where the data is incorporated in the required fashion. 

  • Virtual Operational Data Store 

Also abbreviated as VODS, the method performs further operations. It might be monitoring, reporting or governance of the data assessed through data virtualization. 

  • The VODS collects data virtually from an array of data stores & creates reports. Here, the user gets the information from a pool of sources with no access/worry about the original data storage. 

Benefits of Data Virtualization 

In October 2017, Oracle launched a cloud-backed platform named- Oracle Data Integration Platform Cloud (DIPC). The platform offers data transformation, copy, integration, & data governance. This helps buyers process max yield from large volumes of data sources. 

  • Data virtualization is becoming increasingly popular in the modern database environment. It can provide a high-level abstraction layer that can be used to access and manage data across heterogeneous systems. 
  • It has been found that data virtualization can help reduce complexity in BSS databases by abstracting data access (date, place, format, etc.)- which otherwise becomes a very humdrum task when scaling modern databases. 
  • Real-time data & its instant accessibility really help in taking crucial business decisions for powerful BI & analytics. Moreover, data integration from diverse sources lets information from data lakes, marts, legacy bases, etc. converge within a single, digital layer. 
  • Additionally, it accommodates new data sources. The process adds them virtually to the enterprise data warehouse.  
  • Also, as there’s a central access point for data, enhanced authorization management gives a better security experience & better key performance metrics. Faults in the system can be found & fixed quickly. 
  • Global metadata helps in providing a deep insight of the organization’s data through- data lineage & metadata catalogs. 

As per a report by Gartner in 2017, businesses that use data virtualization for integrating data from various resources will save 40% compared to conventional data integration. 

Conclusion: Start Using Data Virtualization to Boost Your Data-driven Decisions 

Data virtualization offers benefits like high data-quality, improved data management, & speedy time-to-market. 

Thus, to handle the ever-increasing data, data virtualization is an agile data integration approach. This way you can retrieve up-to-date. Information from the sources at an unified window. 

At Echelon Edge, we help in fast data-driven BSS development through data virtualization & take care of every data integration aspect of your business. 


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