Tuesday, July 29, 2008
The Good Data Public Beta is Out!
Go to or website and sign up. And please remember, that we would love to hear from you via our GetSatisfaction forum. Please let us know what you think and help us to create vital community around our product. Thanks!
Thursday, July 24, 2008
Good Data Beta is Close!
I just noticed this article. The UI screenshots are a bit outdated. Yep, 3 months are deep history in SaaS. :-)
Stay tuned, we are close to our first public beta release. Hopefully we will release the public beta next week. If you can't wait and promise me tons of feedback, let me know at zd at gooddata.com. Perhaps I can let you in sooner ;-)
Stay tuned, we are close to our first public beta release. Hopefully we will release the public beta next week. If you can't wait and promise me tons of feedback, let me know at zd at gooddata.com. Perhaps I can let you in sooner ;-)
Friday, June 6, 2008
Does SAAS-BI make sense?
I recently came across this interesting article on the poeticcode blog. In short, it's author claims that BI as service (SAAS-BI) does not make sense because of the difficulties with incremental data loading and higher network bandwidth requirements.
I do not want to dispute here the difficulty of the incremental data warehouse loading. It is difficult in certain situations. It is not that difficult in others where the nature of data help solving it in elegant ways. Moreover the incremental loads are necessary for many BI applications no matter if these are deployed in house or as a hosted service. This integration "baseline" (from the labor and cost standpoint) is the same for both in-house and SAAS. SAAS then removes the labor and costs associated with the data warehouse and analytical stack implementation/maintenance. The multi-tenancy leads to improved HW utilization. Only these two factors lead to huge savings and far better return of investment.
The Internet network connection bandwidth argument is ridiculous: "Not to mention, all the extra network bandwidth needed to encrypt and transfer the data from your data center to the SAAS-BI data center. That also means factoring your internet pipes for much more peak-bandwidth else your potential customers visiting your corporate website might have network problems and worse, you might lose sales and loyal customers."
This argument does not even apply to my naively and quickly implemented FAN (Family Area Network). :-)
Summary: It is certainly good to know about the data integration issues associated with the (SAAS) BI. You should not overlook them. However, I do not believe that these issues are the key decision points like cost of ownership, risk management, return on investment, implementation time etc.
I do not want to dispute here the difficulty of the incremental data warehouse loading. It is difficult in certain situations. It is not that difficult in others where the nature of data help solving it in elegant ways. Moreover the incremental loads are necessary for many BI applications no matter if these are deployed in house or as a hosted service. This integration "baseline" (from the labor and cost standpoint) is the same for both in-house and SAAS. SAAS then removes the labor and costs associated with the data warehouse and analytical stack implementation/maintenance. The multi-tenancy leads to improved HW utilization. Only these two factors lead to huge savings and far better return of investment.
The Internet network connection bandwidth argument is ridiculous: "Not to mention, all the extra network bandwidth needed to encrypt and transfer the data from your data center to the SAAS-BI data center. That also means factoring your internet pipes for much more peak-bandwidth else your potential customers visiting your corporate website might have network problems and worse, you might lose sales and loyal customers."
This argument does not even apply to my naively and quickly implemented FAN (Family Area Network). :-)
Summary: It is certainly good to know about the data integration issues associated with the (SAAS) BI. You should not overlook them. However, I do not believe that these issues are the key decision points like cost of ownership, risk management, return on investment, implementation time etc.
Tuesday, May 20, 2008
Friday, April 11, 2008
See Gooddata live!
We posted the first Gooddata product video on our website. Please bear in mind that we are sharing it early. It is not even alpha. Check it out and let us know what you think.
Wednesday, March 19, 2008
Just-in-Time vs. Just-in-Case BI Costs
Do you know how much power your BI really needs? More precisely, how much power it needs today at 9 AM, next weekend, and at the last day of the quarter or year? Have you bought the ultra-super-duper machine that handles even the highest usage spikes with ease? Or have you decided to sacrifice performance during these peak hours? Do you wait or waste?
Gooddata approach to this dilemma can be described with two keywords: Stateless & Virtualized.
The Stateless is about our architecture. Our product relies on six generic stateless services. The stateless is important for scalability. We can dynamically add any of the six generic service instances as we need to increase throughput of our BI platform.
Virtualized is how these services are deployed. Virtualization allows us to flexibly add hardware nodes to our computing cloud. We have images of different virtual nodes on hand. We can create a new node and dynamically add it to our computing cloud. The beauty is that this all can happen in just few minutes. And the decommissioning of such node is even faster.
We (and you, as our customer) pay for CPU ticks and storage, so the Stateless & Virtual gives you unmatched cost efficiency. Gooddata offers you access to unlimited computing resources. You can get as much of CPU, storage and network bandwidth as you need. And you pay only for what you are really consuming.
Pay for your BI project on Just-in-Time not on Just-in-Case basis.
Gooddata approach to this dilemma can be described with two keywords: Stateless & Virtualized.
The Stateless is about our architecture. Our product relies on six generic stateless services. The stateless is important for scalability. We can dynamically add any of the six generic service instances as we need to increase throughput of our BI platform.
Virtualized is how these services are deployed. Virtualization allows us to flexibly add hardware nodes to our computing cloud. We have images of different virtual nodes on hand. We can create a new node and dynamically add it to our computing cloud. The beauty is that this all can happen in just few minutes. And the decommissioning of such node is even faster.
We (and you, as our customer) pay for CPU ticks and storage, so the Stateless & Virtual gives you unmatched cost efficiency. Gooddata offers you access to unlimited computing resources. You can get as much of CPU, storage and network bandwidth as you need. And you pay only for what you are really consuming.
Pay for your BI project on Just-in-Time not on Just-in-Case basis.
Friday, March 14, 2008
Gooddata Collaborative Analytics
US dollar exchange rate goes steadily down for more than 5 years. This works for us who buy our gadgets in the US. We use the "Zasilkova Sluzba" service to deliver stuff to our doorstep in Czech Republic.
However, the declining dollar doesn't make us happy as entrepreneurs. It makes all resources that we buy in Europe more expensive. We sell our products for dollars and buy our resources mostly for Czech crowns and getting less and less bang for one dollar. I mean 100% less bang since 2002.
Fortunately we are the "analytics guys" so we can predict the future and actively hedge ourselves against the declining US currency. Our latest research shows that US dollar reaches zero sometimes around 6/18/2012.
Knowing this, we can optimize our financial operations and get the most out of it. Tons of gadgets plus nice access to local resources.
DOES THIS RING SOME BELL? Have you seen such a "great" analysis before? Numbers are right, their interpretation is absurd. That is why we focus on collaborative analytics. Collaboration works great in such cases. You bet that I'm going to see a bull*it tag and some lampoon comments regarding my brainpower a few seconds after I publish such analysis to the Gooddata platform. The product separates wheat from the chaff using collaboration capabilities like tag rating and commenting .
P.S.: Roman, I apologize for stealing your idea with the dollar analysis. I can't resist. At the end this is also a bit about collaboration. You invented and designed it and just I implemented it. :)
However, the declining dollar doesn't make us happy as entrepreneurs. It makes all resources that we buy in Europe more expensive. We sell our products for dollars and buy our resources mostly for Czech crowns and getting less and less bang for one dollar. I mean 100% less bang since 2002.
Fortunately we are the "analytics guys" so we can predict the future and actively hedge ourselves against the declining US currency. Our latest research shows that US dollar reaches zero sometimes around 6/18/2012.
Knowing this, we can optimize our financial operations and get the most out of it. Tons of gadgets plus nice access to local resources.
DOES THIS RING SOME BELL? Have you seen such a "great" analysis before? Numbers are right, their interpretation is absurd. That is why we focus on collaborative analytics. Collaboration works great in such cases. You bet that I'm going to see a bull*it tag and some lampoon comments regarding my brainpower a few seconds after I publish such analysis to the Gooddata platform. The product separates wheat from the chaff using collaboration capabilities like tag rating and commenting .
P.S.: Roman, I apologize for stealing your idea with the dollar analysis. I can't resist. At the end this is also a bit about collaboration. You invented and designed it and just I implemented it. :)
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