Engineering & Product Development: SaaS and Big Data
As ephemeral as cloud service might seem, developers and designers have to come up with solid, innovative solutions for data storage and analysis. After all, what goes into the cloud has to be retrieved, and it should be retrieved in a meaningful way. It also needs to be retrieved efficiently. What solutions have engineers come up with?
Back in 2012, Raj De Datta, co-founder of Bloomreach, published a piece in TechCrunch that predicted the fall of SaaS (Software as a Service) and the rise of BDA’s (Big Data Applications). His reasoning was fairly sound, stating that while SaaS only provide organizations with internal data, BDAs provide organizations with industry data. This allows organizations to track competitor trends and financials as well as their own.
At the very end of the article, before De Datta exclaimed “Hello BDAs, Goodbye SaaS.” He mentioned that some SaaS companies might survive the transition to big data if they adapt.
Guess what? Some adapted. With more and more SaaS providers adopting database management technologies, these software providers are capable of providing their users with powerful big data analytics.
SoftwareAG is one company that has merged predictive analytics and data streams into a highly effective software platform that operates in the cloud as well as within on-premise IT sites. According to eWeek, SoftwareAG engineers built a platform with:
support for Docker containers [that] helps Apama users deploy and use the Apama platform consistently in on-premise and cloud environments.
This means data is readily compiled, analyzed and pulled for informed decision-making. Whether stored in the cloud or an on-premise server, when integrated with database management systems and supportive software platforms, both small and large companies are able to access data streams (with data from both internal and external sources) and filter that data through predictive analytics tools customized for their organization.