In my last post, I explained what data virtualization is and described its benefits. In essence, data virtualization is an agile data management solution for data integration projects. So, what type of problems can data virtualization solve? Let’s look at some use cases.
- 1You are working for an organization, and a new business line wants to develop a data-oriented application. Unfortunately, your organization doesn’t have the time and money required to develop a new data warehouse or data mart. The only way to quickly create a new application at low cost is with data virtualization software.
- 2You’re working on a project that requires data integration between an application, a data warehouse, and real-time data being generated by an operational data source.
- 3You’re working for a BI-focused organization with multiple, redundant ETL tools. Each ETL tool has a different UI and visual presentation, and there is no common access mechanism. A data virtualization software solution would give you access to the same data using any BI tool.
- 4You need to integrate data from external sources such as a public website, social networking sites like Twitter and Facebook, and regulatory/ compliance data to build an on-demand, real-time data access solution.
- 5You have difficulty replicating data and want to overcome those constraints and challenges. For example, the need to access regulatory/compliance databases can cause data-replication constraints.
- 6You want to build a “single version of truth” or 360-degree view for a customer with data spread across multiple databases (e.g., purchase orders, weblogs, and other master and reference databases).
- 7You have several downstream applications that are mission critical, so you need to migrate data without disrupting these applications.
- 8You want to build a solution that combines internal data with structured and unstructured data from a public cloud application.
- 9You’re working on a project that requires a common interface to data, regardless of its physical location. The data might reside in the cloud, in files, in operational applications, in web applications, or in data warehouses, causing a potential performance bottleneck when users try to access the data.
- 10You need real-time analytics to create fast, cost-effective reporting solutions.
Data virtualization is the answer for any organization that needs to quickly and flexibly create BI solution. Of course, data virtualization is not the solution for every project, and it cannot completely replace BI. But it can help enterprises develop solutions that help them more quickly make sound business decisions. In my next post, I’ll address the concerns some IT folks have about the performance of data virtualization solutions.