Recommendations to others considering CData Virtuality:
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. Review collected by and hosted on G2.com.
What problems is CData Virtuality solving and how is that benefiting you?
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. Review collected by and hosted on G2.com.