MicroStrategy on Amazon Web Services (AWS) Cloud

Editor's Notes

• #3: So when looking at Cloud as a whole, you can separate it into these 3 different tiers, IaaS – you are getting a server with an operating system and you are paying for a hardware replacement and can install whatever you want on top of that. One tier higher is PaaS, now you are taking a machine and installing a software platform on top of it. MSTR Cloud Enterprise is PaaS. The highest level is the software as a service this is an application that has been developed for a specific purpose MSTR Cloud Personal and Cloud Express for example are our offerings.
• #5: MSTR Cloud is giving you those 2 bottom areas which allow you to develop any applications you want for both web or mobile.
• #7: There are 2 options you have to connect the MSTR Cloud to your data. Typically you would have your data contained in an on premises data center of course it can also be contained in a Cloud somewhere else. So the first option here is Direct Connect – This is when a user chooses to only run the MSTR BI layer in the cloud. The intelligence server is running in the MSTR Cloud, The In-memory cubes and cache running in the cloud and then what we do is establish a secure VPN into the on premises datasources. This enables us to run queries directly against these db’s through the VPN connection and our Cloud becomes a part of their network and it is a very easy way for a user to get started with MSTR Cloud. The other option is where again we set up that VPN connection and through our ETL capabilities using Informatica to move data and populate a Cloud warehouse which is running in our Cloud as well. The BI layer then communicates directly with that Cloud warehouse to run queries and from that architecture we see very good performance. There are a couple of different options there. Worth noting in that direct connection model; it results in very good performance. Even though the BI layer is geographically separated from the on premises data center. We are taking advantage of caching, clustering, 64 bit, in-memory BI, the idea of pushing analytics down to the db, running queries in the db, and then returning a minimum result set back up into the cloud, leveraging our multipass SQL and multisource db capabilities.
• #8: What does the cloud offering Include? The MSTR Cloud goes beyond just BI, we do have Cloud based BI based on the Enterprise platform with full enterprise functionality; its highly scalable but we also incorporate a analytical DB option and a cloud ETL or data integration option. We offer a range of different tiers of databases from small scale databases with a cost effective option to very large 100TBs of data running on dedicated high performance db appliances. And then ETL we offer high throughput parallel data loading capabilities which allows customers to integrate their data which may reside on premises or alternatively on another Cloud based service.
• #9: We have partnered with best of breed providers to offer business intelligence, DB and Etl to our users
• #11: MSTR Cloud is giving you those 2 bottom areas which allow you to develop any applications you want for both web or mobile.
• #13: There are 2 options you have to connect the MSTR Cloud to your data. Typically you would have your data contained in an on premises data center of course it can also be contained in a Cloud somewhere else. So the first option here is Direct Connect – This is when a user chooses to only run the MSTR BI layer in the cloud. The intelligence server is running in the MSTR Cloud, The In-memory cubes and cache running in the cloud and then what we do is establish a secure VPN into the on premises datasources. This enables us to run queries directly against these db’s through the VPN connection and our Cloud becomes a part of their network and it is a very easy way for a user to get started with MSTR Cloud. The other option is where again we set up that VPN connection and through our ETL capabilities using Informatica to move data and populate a Cloud warehouse which is running in our Cloud as well. The BI layer then communicates directly with that Cloud warehouse to run queries and from that architecture we see very good performance. There are a couple of different options there. Worth noting in that direct connection model; it results in very good performance. Even though the BI layer is geographically separated from the on premises data center. We are taking advantage of caching, clustering, 64 bit, in-memory BI, the idea of pushing analytics down to the db, running queries in the db, and then returning a minimum result set back up into the cloud, leveraging our multipass SQL and multisource db capabilities.