There is an explosion of data being generated by cloud applications like Salesforce.com, Adobe Analytics, and HubSpot. In addition, enterprises are increasingly migrating their data to cloud with services like Dropbox, DocuSign, Google, AWS S3, and AWS RDS.
While enterprises have adopted Software as a Service (SaaS) for applications; the move to BI as a service has been slower. This trend is about to change and IDC predicts that by 2020, 50% of business analytics software will incorporate predictive analytics based on cloud platforms.
The definition of cloud BI would vary based on whom you talk to. First you have the traditional enterprise BI vendors; who have ability to host their software on a cloud server and call it a cloud service. Then you have the next generation BI vendors that have designed their software from ground up to use the elastic cloud services of Microsoft, AWS, and Google and offer real cloud BI service. AWS QuickSight falls under the second category of cloud BI vendors. Here are some of the popular cloud BI vendors Microsoft Power BI, Looker, Chartio, and Bime.
There are several operational and financial drivers that work in favor of cloud BI service, the key ones being:
Speed of implementation and deployment: Infrastructure and software are available immediately provisioned exactly as required for the BI service
Elasticity: Leveraging the compute power that can be scaled up or down on-demand based on business needs
Lower total cost of ownership: It significantly reduces the infrastructure and related operational expenses
Improved connectivity: For enterprises that already have moved to cloud for hosting their applications, the cloud BI is evolution and is the next step in their journey to be more cloud native
Next we will look into what makes AWS QuickSight stand out when compared to the others.