Comments on: Web Analytics Data Sampling 411 http://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html Pluralitas non est ponenda sine neccesitate. Tue, 16 Mar 2010 15:01:56 +0000 http://wordpress.org/?v=2.9.2 hourly 1 By: Conciliando datos de diferentes herramientas « Blog2puntocerohttp://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html/comment-page-1#comment-480385 Conciliando datos de diferentes herramientas « Blog2puntocero Tue, 06 Jan 2009 16:19:42 +0000 http://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html#comment-480385 [...] La presentación de informes en tiempo real, basados en grandes volúmenes de tráfico, son la principal justificación para la utilización de esta técnica que, siendo más precisos, presenta diferentes variantes que pueden dotarla de mayor protagonismo (recomiendo este post para profundizar en este tema).La carrera de obstáculos, invita a pensar que la situación ideal pasa por la utilización de una única herramienta. Avinash hizo hace unas semanas un checklist muy interesante al respecto en su blog. [...] [...]
La presentación de informes en tiempo real, basados en grandes volúmenes de tráfico, son la principal justificación para la utilización de esta técnica que, siendo más precisos, presenta diferentes variantes que pueden dotarla de mayor protagonismo (recomiendo este post para profundizar en este tema).

La carrera de obstáculos, invita a pensar que la situación ideal pasa por la utilización de una única herramienta. Avinash hizo hace unas semanas un checklist muy interesante al respecto en su blog.
[...]

]]> By: Avinash Kaushikhttp://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html/comment-page-1#comment-162607 Avinash Kaushik Tue, 10 Jul 2007 05:11:20 +0000 http://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html#comment-162607 <b><font color=blue>c0t0s0d0 : </b></font> How delightfully clever!!!I don't have your real email address but please consider this as my thanks for coming back and helping clear up the mystery. That was kind of you.-Avinash. c0t0s0d0 : How delightfully clever!!!

I don't have your real email address but please consider this as my thanks for coming back and helping clear up the mystery. That was kind of you.

-Avinash.

]]> By: Stevehttp://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html/comment-page-1#comment-162604 Steve Tue, 10 Jul 2007 05:02:31 +0000 http://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html#comment-162604 Well it's a little unfair to Dylan... :-)<blockquote> c0t0s0d0 = cylinder zero, track zero, slice zero, disk zero </blockquote>Urm. No actually. :-)For starters it should be: c0t0d0s0. c == controller t == target d == drive s == sliceThis is a "partition" identifier. Not a position on disk identifier. That would be pointless at this level.Target is the SCSI ID. When you use the format command, you drop the slice to work with disks and hence set up your slices (or partitions).eg: <code> # format ... 0. c0t0d0 /pci@1f,4000/scsi@3/sd@0,0 1. c0t1d0 sol_8 /pci@1f,4000/scsi@3/sd@1,0 2. c0t2d0 /pci@1f,4000/scsi@3/sd@2,0 ... </code>Three very different 9G SCSI drives on the one backplane. You might even decode some of that from the /pci... address too. :-)Speaking as someone who still is a Solaris sysadmin and has been for about 15 years. :-)Cheers! Well it's a little unfair to Dylan… :-)

c0t0s0d0 = cylinder zero, track zero, slice zero, disk zero

Urm. No actually. :-)

For starters it should be: c0t0d0s0.
c == controller
t == target
d == drive
s == slice

This is a "partition" identifier. Not a position on disk identifier. That would be pointless at this level.

Target is the SCSI ID.
When you use the format command, you drop the slice to work with disks and hence set up your slices (or partitions).

eg:

# format
...
0. c0t0d0
/pci@1f,4000/scsi@3/sd@0,0
1. c0t1d0 sol_8
/pci@1f,4000/scsi@3/sd@1,0
2. c0t2d0
/pci@1f,4000/scsi@3/sd@2,0
...

Three very different 9G SCSI drives on the one backplane. You might even decode some of that from the /pci… address too. :-)

Speaking as someone who still is a Solaris sysadmin and has been for about 15 years. :-)

Cheers!

]]> By: c0t0s0d0http://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html/comment-page-1#comment-162467 c0t0s0d0 Tue, 10 Jul 2007 02:07:09 +0000 http://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html#comment-162467 <blockquote>PS: Dylan Lewis loves riddles, I should ask him to see if he can solve what c0t0s0d0 stands for!! :)</blockquote>c0t0s0d0 = cylinder zero, track zero, slice zero, disk zero (from my solaris admin days :-)

PS: Dylan Lewis loves riddles, I should ask him to see if he can solve what c0t0s0d0 stands for!! :)

c0t0s0d0 = cylinder zero, track zero, slice zero, disk zero (from my solaris admin days :-)

]]> By: maxhttp://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html/comment-page-1#comment-155394 max Tue, 03 Jul 2007 12:17:39 +0000 http://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html#comment-155394 Very insightful session, and clear that progress has been and continues to be made in this area. That said, there remains a HUGE gap in the dialog. When we talk about how to draw meaningful conclusions from statistically relevant samples of the data, we can't forget about the underlying data quality to begin with. If, for example, the data itself has an inherent error rate which renders it statistically impaired, then no amount of sampling, however precise or sophisticated, will be able to restore statistical significance. A lot can and routinely does go wrong at the source which undermines all efforts flowing from it. For example, tags can be missing entirely. If they're not missing, they can be inoperable (e.g., due to syntax errors and the like). If they're operating properly, they can be generating inaccurate variables. If the variables are accurate, the beacon parameters can be wrong. These are not hypotheticals. The incidence of such errors is shocking (error rates average well over 25% for relatively sophisticated practitioners - CODE SUPER BRIGHT RED!). And by the way, this is "systemic" error and not "random" error, so the affects of such poor data quality cannot be made up through quantity. The implications are profound. Refining sampling methods is absolutely necessary for many reasons, but in truth, doing so without concurrently addressing the underlying data quality problems is a whole lot like painting over dirt. Very insightful session, and clear that progress has been and continues to be made in this area. That said, there remains a HUGE gap in the dialog. When we talk about how to draw meaningful conclusions from statistically relevant samples of the data, we can't forget about the underlying data quality to begin with. If, for example, the data itself has an inherent error rate which renders it statistically impaired, then no amount of sampling, however precise or sophisticated, will be able to restore statistical significance. A lot can and routinely does go wrong at the source which undermines all efforts flowing from it. For example, tags can be missing entirely. If they're not missing, they can be inoperable (e.g., due to syntax errors and the like). If they're operating properly, they can be generating inaccurate variables. If the variables are accurate, the beacon parameters can be wrong. These are not hypotheticals. The incidence of such errors is shocking (error rates average well over 25% for relatively sophisticated practitioners – CODE SUPER BRIGHT RED!). And by the way, this is "systemic" error and not "random" error, so the affects of such poor data quality cannot be made up through quantity. The implications are profound. Refining sampling methods is absolutely necessary for many reasons, but in truth, doing so without concurrently addressing the underlying data quality problems is a whole lot like painting over dirt.

]]> By: anonymoushttp://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html/comment-page-1#comment-154374 anonymous Mon, 02 Jul 2007 15:24:22 +0000 http://www.kaushik.net/avinash/2007/06/web-analytics-data-sampling-411.html#comment-154374 I think you may have forgotten one. I work with a vendor who can apply a percentage governor to the JS lib file and cookie a sample of the UVs hitting the site. if the % is set to 10 then 1/10 of the UVs are tracked. This is a bit different that what you explain or how I understood your explanation so I might have missed something.It seems closest to the ORANGE method but not sure since you imply its page based vs. UV based. the code JS still sends data for every page but for only a % of the UV traffic based on a cookie identifier. You can even create new metrics based on the sample to get up to almost normal levels by creating a multiplier on UVs or PVs. I think you may have forgotten one. I work with a vendor who can apply a percentage governor to the JS lib file and cookie a sample of the UVs hitting the site. if the % is set to 10 then 1/10 of the UVs are tracked. This is a bit different that what you explain or how I understood your explanation so I might have missed something.

It seems closest to the ORANGE method but not sure since you imply its page based vs. UV based. the code JS still sends data for every page but for only a % of the UV traffic based on a cookie identifier. You can even create new metrics based on the sample to get up to almost normal levels by creating a multiplier on UVs or PVs.

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