The Critical Role of Data Virtualization in Modern Businesses
Businesses today are more complex and interconnected than ever before. At the core of any responsive business, there are vast volumes of data, sourced from diverse channels including financial systems, human resources systems, and market analytics, among others.
This volume of information has the potential to revolutionize a company by enabling decision-makers to adjust with precision and foresight based on impactful, real-time data. Managing intricate business processes and the massive amounts of data coming in from a variety of systems is complex and without the proper tools to manage it all, the potential will remain untapped, and the information underutilized.
Because of this known complexity, fewer organizations have been able to achieve the visibility required to differentiate and excel in their business operations. This lack of visibility costs organizations millions of dollars each year and highlights why successfully leveraging this data is critical for business leaders looking to boost productivity, reduce costs, and provide an overall better customer experience.
Comparing Data Lakes and Data Virtualization
In the early 2010s, data lakes and data virtualization emerged as two popular types of data solutions for businesses to address the challenges of storing and analyzing data. Each of these solutions takes a unique approach of how to handle large volumes of data coming from multiple sources.
Data lakes store raw data without predefined structures, while data virtualization provides adaptable access to various data sources such as cloud storage, databases, legacy systems, and application programming interfaces (APIs). With companies prioritizing the agility of real-time data access and improved data governance, data virtualization has since gained widespread adoption.
The Benefits of Data Virtualization
Data virtualization provides a logical view of multiple data sources, improving data access and integration, and eliminating replication. This benefits businesses by offering a unified, real-time view of data from various sources, allowing them to make more informed decisions by streamlining both data and processes.
Data virtualization technologies create a flexible layer above different data sources, integrating information in real-time without the need to move data physically. This approach delivers four key benefits:
- Quicker access to critical data. Virtualization enables managers to instantly access and analyze information by combining data from multiple legacy systems and databases to guide decision-making. This removes the need for lengthy data replication projects, allowing for vital flexibility.
- A single source of truth. Data virtualization allows teams to access consistent, unified information instead of questionable data from multiple separate sources, creating one source of truth and leading to increased data reliability and improved operational efficiency.
- Flexibility and scalability. Businesses are constantly evolving through the generation of new information and the implementation of new systems. Data virtualization's abstraction layer actively accommodates these changes, allowing seamless access to new data sources without disruption. The architecture also scales to handle growing data volumes as business networks expand.
- Reduced costs. Because data virtualization does not require moving and replicating data, it eliminates the overhead of traditional extract, transform, and load (ETL) processes. Less data replication means lower infrastructure and licensing costs. Teams also save time by not having to manually move and synchronize data.
With data volumes in business growing quickly and new data sources emerging via Internet of Things (IoT) sensors and blockchains, data virtualization has emerged as an impactful, cost-effective strategy to integrate and deliver trusted data to key decision makers.
Starting the Data Virtualization Process
The data—and the implications for data—in businesses will only continue to expand. The ability to harness its power will also only continue to grow, making now a great time for leaders to explore data virtualization for their organizations. Utilizing the self-assessment questions listed below will assist in creating a thorough data virtualization evaluation and provide a starting off point—assessing the current infrastructure and information needs of the company.
Answering important what, why, and how questions will help develop a compelling business case for this modern data-driven approach. Implementing the right strategy, transformation roadmap, and solutions will empower businesses with the data visibility and responsiveness needed to excel in today's dynamic, global, and challenging business environment.
BUILT Data Virtualization: Self-Assessment Questionnaire
1. Is there a clear understanding of all of the key business data sources across our organization?
2. Is the enterprise data simple to access—even when it is spread across multiple systems?
3. Is the enterprise data consistent and reliable in providing effective reporting and analysis?
4. Do we have a unified view of enterprise data that enables us to make impactful operational decisions?
5. Can we quickly access our integrated enterprise data to respond to business disruptions?
6. Do we have a complete picture of our operations available in real-time?
7. Can we combine data from multiple systems today to get detailed insights?
8. Is our operational data secure and properly governed?
9. Do we have excellent in-house skills in designing, modeling, deploying, and managing our data?
10. Has access to integrated, real-time data allowed us to reduce costs?
11. Do we have a data virtualization strategy as part of our overall data management roadmap?
12. Is the company committed to improving data integration?
13. Is becoming data-driven a top strategic priority for our organization?
For more information on BUILT’s data virtualization capabilities, and to talk with one of our digital transformation experts, go to www.builtglobal.com/contact.
About the author: With over 25 years of experience as a Global Business and Digital Transformation Executive, Alejandro has successfully driven large-scale initiatives for end-to-end supply chain and manufacturing operations. His focus has been on utilizing cloud and cutting-edge technology to optimize processes and enable more efficient operations for Top 500 blue chip industrial and technology enterprises.
