With the increased production of data from various sources and in a variety of forms, traditional ETL methods simply can’t keep up with the large and constantly evolving untraditional data sources being created. As such, the cost of maintaining a data warehouse has become expensive and its management extremely cumbersome.
The Case for Virtual Data Warehouses
Depending on a company’s requirements, virtualization can reduce the cost of keeping data warehouses. Virtual Data Warehousing delivers near real-time insight using fewer resources and points to your structured and unstructured data without copying or moving it, but instead stores only the index to the data. What does this mean?
You don’t need to ingest massive amounts of data, unlike traditional ETL methods.
Whereas a traditional data warehouse provides a central repository for information, a virtual data warehouse uses middleware to build direct connections among disparate applications. This virtual approach requires less time and expense to develop, and entails less risk of data being lost.
In a nutshell, virtual data warehouses enable analysts to make better decisions by allowing users to:
- Search on live data to make decisions in near real time
- Deploy quickly and efficiently without the expense or effort of setting up a traditional data warehouse
- Lower the total cost of ownership to as little as one-third of alternate methods, freeing IT teams to focus on high-impact projects
Our belief here at Modemetric is the future of BI very much involves business users being able to be owners of their own data. If you’re interested in taking control of your analytics, sign up for our Harmonize Your Data with Code Mapping webinar on September 19th. This webinar will demonstrate how to to easily add new dimensions to existing data models without IT help or consolidate data from different sources on the fly.