If you leave al the categories ON and subtract out -NEO -APARTMENTS from the Vertica query it shows the edge as described above.

Obviously, PROPER analysis needs to be done. The study I am suggesting with sentiment would go against the blogopshpere, social media, youtube, and news to categorize the topics and then mine the text for discourse.

A metric on Search volumes is very interesting but the lacks the beef. Is it “Directionally correct?”, “Why are they searching?”, “Who is searching?”, “What event prompted the search?”, “What is the sentiment of the results of the search?”, “What’s in the news?”, “What are the bloggers and tweeters saying?”, “What Sentiment do the comments of the blogs bring?”

A long way to go, I know. I hope that others with a passion in this space can help interpret the data. The current platforms are maturing in this free text analysis area, but they are expensive and seriously lacking. (More on this to come)

Thanks

I just re-ran your graph selecting only the category “computer and electronics” and you’ll see that vertica winds up below Greenplum. Relatively speaking, Greenplum, Vertica, Infobright and Paraccel are quite close while as one would expect Teradata and Netezza are quite a bit higher.

Yes you are right about a community in Miami. When I first saw “NEO VERTICA” it really through me for a loop and my mind went right to Neoview. It is in fact an up and coming (at least from a search standpoint) phrase. Looking at the relative #’s on the 100 point scale, it showed a top of about 3 and the searches were conducted primarily in 2008. So I did not take it out because the “Jist” of the analysis would theoretically be the same. I am looking now at the impact of “Vertica Apartments” because that phrase had search spill over into 2009 can skew the numbers. I would like to get the “Vertica Apartments” out of this analysis and see what it looks like. Stay tuned.

I would however want to focus on “REAL” inquiry based terms to bring some accuracy to this type of study.

Thank you for your comment. I will dive a little deeper to see if I can normalize this a little bit more.

Charlie

Yes you are right about a community in Miami. When I first saw “NEO VERTICA” it really through me for a loop and my mind went right to Neoview. It is in fact an up and coming (at least from a search standpoint) phrase. Looking at the relative #’s on the 100 point scale, it showed a top of about 3. So I did not take it out because the “Jist” of the analysis would theoreticall be the same.

I would however want to focus on “REAL” inquiry based terms to bring some accuracy to this type of study.

Thank you for your comment. I may dive a little deeper to see if I can normalize this a little bit more.

Charlie

I did see something which may be skewing your analysis quite a bit in reference to Vertica. When you look at the search terms included in the overall analysis for Vertica you see a number of them that don’t refer to the database company, but is apparently the name of an apartment property management company in Canada. That is why Canada shows up as the number 1 region of interest for Vertica.

I don’t know whether there is a way to exclude that to get a more accurate picture. I added my company Infobright to this analysis to see where we stood (right now looks like between Greenplum and ParAccel) but I am not sure what the data would look like if Vertica excluded non-company searches.

Regards…