birst automated business intelligence (bi)

Deploying Business Intelligence (BI) solutions quickly and cost effectively

Conventional Business Intelligence (BI) solutions require IT to cobble together a set of disparate tools from different vendors (or different products from the same megavendor), resulting in long implementation times, staggering services and software costs, and high failure rates. As a result, BI is often limited to the few large companies that can afford it – implementations are inflexible, limited in scope, and used by very few people.

Birst provides a high degree of automation in a single product that addresses traditional challenges to cost effectively and quickly deploy BI solutions. Birst automates many of the resource intensive and time consuming manual tasks needed to deploy and maintain a BI solution using conventional Business Intelligence (BI) tools.

Birst BI lifecycle automation

Birst takes care of automatically generating and maintaining all facts and dimensions tables, join relationships and the required processes for loading into an analytical data store. The advantage of automation is that it enables rapid iterative development of an analytical data store by enabling IT to focus on the logical model underlying the business processed to be measured and not the physical instantiation of it.

Birst compiles a logical dimensional model into a fully modern star schema design. Logical measures are automatically analyzed for calculation grain, while logical dimensions are analyzed for levels requiring persistence. Facts are automatically generated, while dimensions and mini-dimensions are created as needed. Birst generates and manages all key relationships including surrogates where necessary.

Birst BI automation does not stop at generating an analytical data store for you. To help users quickly explore data relationships, Birst can also automatically generate a series of data exploration dashboards based on an input data set. These Quick Dashboards allow users to very quickly explore their data sets and identify patterns before beginning to build out end-user reports and dashboards. This allows for rapid prototyping and more focused requirements definitions.

Next Steps
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