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Who Is Birst
- 2. 1,000+ Organizations Using Birst Confidential 2
- 3. Business Analytics is Hard Because Business Is Complex • The part you see, dashboards, charts, etc. is just the icing on the cake • It’s the collection, combination, integration, de/coding, transcribing and cleansing of organizational data into a usable format that is hard • Doing so on a repeated basis, over time is harder • Business rules rarely allow you to just “add-up” data Confidential 6/2/2012 5
- 4. So, the problem has been broken into pieces, solved by a series of individual products Traditional BI - Powerful insight enables better decisions BUT - Expensive to buy - Time consuming to set up ETL Extract Data OLAP Reporting Engine(s) Users Transform & Load Warehouse Engine Ad Hoc Reporting Finance Data CRM Dashboards Data Operations Data More Printed Reports Data 6/2/2012 6
- 5. Confidential
- 6. As a result, there have generally been two BI camps BI Suites Capability Agility Confidential 6/2/2012 8
- 7. Modern Approach via Birst Confidential 6/2/2012 9
- 8. Our Platform Redux Confidential 6/2/2012 10
- 9. Birst Turns BI Model Upside Down Traditional BI Birst • Birst turns BI on its Deployment Deployment head & automates BI – Top-down approach automatically generates warehouse – Full-featured ETL Data Data enables endless Warehouse Warehouse customization ETL ETL • This approach is: – The ONLY way to do full BI as a service – The ONLY way to provide full BI more economically Confidential 11
- 10. Birst Customers Integrate Data From Confidential 6/2/2012 12
- 11. Typical BI Timeline (Months) Source N (DB, File, XML) 2 6 2 2 1 1 1 Cube MSAS Hyperion Birst Timeline (Months) 2 1 p Requirements / Logical Model pETL p Data Validation pPhysical Modeling pReport Development pReport Validation p Data Visualization & Security Confidential 6/2/2012 13
Editor's Notes
- This is why we are disrupting the market. People don’t want more SAP or Oracle
- End users’ requirements for insight always increase over time –they need insight into more data sources to build a more complete view of the business and they need more ways to analyze and interact with that data for them to make effective decisions. <click – show Traditional BI curve>Unfortunately, while the pace of requirements change is high, traditional BI is very slow to deploy and update/enhance. This means that the first phase deployment is often 6-12 months in duration or even more. Subsequent iterations typically take 6 months or so. This pace of enhancement means that the business users’ requirements will never be fully met – forcing the business users to “fly blind” in key areas and lowering the effectiveness of the overall decision-making process.<click – show Agile BI curve>Agile BI offers a much better way for companies to meet their end users’ demands for insight over time. By enabling rapid initial deployments and more rapid iterations over time, Agile BI enables the end users to explore a more comprehensive view of their business in more flexible ways more quickly and affordably than traditional BI – enabling the BI system to keep pace with the end user requirements over time. <click – show Business Value area graph>By better keeping pace with end users requirements, Agile BI enables better and more effective decision making in more areas of the business more quickly and affordably than traditional BI solutions. This difference enables end users to drive more business value for their organizations over time.
- One of the main drivers of expense in Traditional BI solutions is the overwhelming amount of work required to get the data from the source systems all the way into the analytical engine’s logical model where it can be flexibly analyzed. In traditional systems this means extracting the data from the source systems, transforming it and loading it into a data warehouse in a star schema structure and then mapping the logical model onto that transformed data in the DW. This multi-step process requires a great deal of precision and coordination for it to be successful – and that takes time and $.Birst turns this process on its head. Instead of beginning with the data and moving it towards the logical analytical model via many painful steps, Birst enables the designer to declare the logical model on the source schema – then Birst creates the ETL and the star schema DW automatically. This not only makes initial set up easier, it makes ongoing maintenance easier as changes in the source data can be quickly modeled in Birst and instantiated at every layer of the stack automatically. It also makes it easy far easier to add additional data sources as your needs evolve and new data is required to deliver the necessary business insight.
- Launched in Q4 and is taking offInflection point on product, market