What do you like best?
Having used Data Virtuality for the past 4.5 years, I can say that Data Virtuality is a solution that is both easy to learn and hard to master (in a positive way). The manner in which we have set up our data driven environment has been made possible through Data Virtuality. The logical data warehouse first enabled us to rapidly access and combine many separate data sources in an ad hoc manner and later, provided us with the tools to set up a well structured, fully featured data integration and data warehouse solution.
Data virtuality virtually takes in all data sources and enabled us to process that data for it to be published to any desired client tool, either via a ODBC or JDBC drivers or via the built-in REST service. The support team at Data Virtuality responds very fast and correct to any question and on more than one occasion has gone 'the extra mile' to satisfy our support needs.
What do you dislike?
Additional client tools like Tableau, Looker, Excel or PowerBI are a must for business users - it has proven difficult to learn these users to use SQL to extract data in a flexible manner. Data virtuality requires experience in and understanding of logical data warehouse design or training therein to most effectively use the power that the solution offers.
Recommendations to others considering the product
Ideally, set out a strategy/plan out from the beginning in terms of how to use data virtuality's flexibility to it's full potential (best practices can be delivered to you by the company).
Having trained personnel on board that know their way around data modeling data processing will help a great deal.
What business problems are you solving with the product? What benefits have you realized?
At Springlane, we use Data virtuality for all things data. We integrate data from various data sources to be used company wide for reporting, analysis and forecasting.
Through the connection with many different data sources via one relatively simple query interface, we were first able to respond quickly to most questions that our organization had, by simply querying data for any of the connected systems in an ad hoc manner. This helped tremendously with building up our team as the go-to-source for data, more specifically 'the truth' regarding anything not easily found in application's front ends.
Data Virtuality's use of virtual schemas, powerful transformation and scheduling capabilities, combined with the best practices provides to us by the the support team, enabled us to undertake the next steps we needed to automate many, if not all of the data preparation we previously did manually and add many more features to boot. The virtual schemas support organizing our work, making it easier to share development over multiple developers and share and re-use created code. The transformation capabilities offered us the means to do without any external tools and truly have a single point of reference for our data related projects, whereas the scheduling ties this all together in automated nightly jobs.