In the previous post here I suggested that a SAN-based, cloudy, EDW is about 4X the cost for the same performance over a data warehouse appliance.. and I described why. I have actually seen this comparison. It is difficult to compare Amazon EC2 hardware to the hardware typically assembled in a shared-nothing EDW cluster whether … Continue reading “Cloud Computing and Data Warehousing: Part 3 – ParAccel on EC2”
There is still an open question over whether, after the Big Bang, there is enough mass in the Universe to slow the expansion and cause the universe to contract. While the Big Data Bang continues to expand the universe of bits and bytes… I would like to ask whether some of these numbers are overstated? … Continue reading “The Big Data Bang”
David Linthicum suggests here that Shadow IT is not all a bad thing. He references a PricewaterhouseCoopers study that suggests that 30% of all IT spending comes from the business directly… from outside of the IT budget. In the data warehouse space we can confirm these numbers easily. Just google on “data mart consolidation” … Continue reading “Chaos, Cloud Computing, and the Data Warehouse”
In Part 1 of this topic (here) I suggested that cloud computing has the ability to be elastic… to expand and maybe contract the infrastructure as CPU, memory, or storage requirements change. I also suggested that the workload on an EDW is intense and static to point out that there was no significant advantage to … Continue reading “Cloud Computing and Data Warehousing: Part 2 – An Elastic Data Warehouse”
After a little more thinking I’m not sure that Big Data is a new thing… rather it is a trend that has “crossed the chasm” and moved into the mainstream. Call Detail records are Big Data and they are hardly new. In the note below I will suggest that, contrary to the long-standing Teradata creed, … Continue reading “More on Big Data… and on Big Data Analytics… and on a definition of a Big Data Store…”
Sorry… this is a little geeky… The news and blogs on Exalytics tend to say that Exalytics is an in-memory implementation with 1TB of memory. They then mention, often in the same breath, that the TimesTen product which is the foundation for Exalytics now supports Hybrid Columnar Compression which might compress your data 5X or … Continue reading “More on Exalytics: How much user data fits?”
There is a lot of talk these days about predictive analytics, big data, real-time analytics, dashboards, and active data warehousing. These topics are related in a fairly straightforward way. Further, there are new claims about in-memory database processing that blends these issues into a promise of real-time predictive analytics. Lets tease the topic apart… Predictive … Continue reading “Predictive Analytics, Event Processing, and Rules… Oh, and in-memory databases…”
