A truly next generation platform for enterprise BI and analytics
Birst is the only enterprise business intelligence platform that connects together the entire organization through a network of interwoven virtualized BI instances on-top a shared common analytical fabric. Birst enterprise BI delivers the speed, self-service, and agility front-line business workers demand, and the scale, security, and control to meet rigorous corporate data standards. Birst delivers all of this and much more with low TCO via public or private cloud configurations.
|Rapidly unifies complex data||Broad and complete business visibility, fast|
|Analyze complex processes & models||Real time sync across users and departments|
|Blends centralized and decentralized||Enable local agility with global analyses|
|Trust and reuse key metrics||Values are correct, for ad hoc and scheduled use|
|Users can use a variety of tools||Drive adoption, usage and self-service|
|Fast to value, every deployment||Short time and cost to deploy = lower risk|
|Economically scale, on demand||High performance and superior economics|
Birst incorporated the best-of-breed of all the qualities that we were looking for in a BI solution. The total cost of ownership and the flexibility that Birst provided made us choose Birst over other providers.Ram Nagaraj, Director of IT, Business Intelligence and Master Data, Aruba Networks
Have a complex mix
of enterprise and local data?
No ETL capabilities. Need to go through complex manual process; or via separate tools in the stack (e.g. MSFT).
Automatic Data Refinement (ADR), Live Access, and query federation allow for rapid data combination and refining regardless of changes in data model (new sources, volumes, etc).
Need to go through data extracts, scripting, and or 3rd-party tools (e.g. Informatica).
Looking to analyze local
data but with global views?
Supports end-user data blending via siloed sandboxes or this is not supported at all.
Enable local data enrichment with trusted global views with end-user data blending on networked data.
Offers end-user data blending using data extracts (e.g. TDE files) which are siloed from each other.
Have a multi-step
Analytical consistency within one instance only. Different instances (Projects, Universes, etc.) not networked together.
Networked BI architecture automatically links independent virtual spaces providing analytical consistency across different , linked parts of the company’s value chain.
No way to share a data model across multiple deployments of Tableau or Qlik. Sharing is at the chart level versus data level.
Is there a mix of user experience
needs across business users?
Limited functionality to support different analytic styles and 3rd-party tools.
Adaptive UX and Open Client Interface support different analytic styles (visual discovery, dashboards, reporting, mobile) and 3rd-party tools (Tableau, Excel).
No support for 3rd-party front-end tools.
Need transparent data
governance across the enterprise?
Have to re-implement changes in key calculated metrics or changes in data hierarchies in each individual instance, then test and deploy each one separately.
Semantic layer provides a single source of truth by automatically propagating any changes to the underlying data structure across the whole environment.
Looking for time to value at scale?
Need to account for batch windows, system downtimes, separate physical environments for DEV/UAT/PROD, and manual upgrades.
See value quickly with Always-On, virtual spaces, instant movement between DEV/UAT/PROD, instant upgrades, and value based design.