Kontagent is a type of web analytics that provides creators of social apps insight into how the app is being used, spread, and by what type of people.  The company isn't currently positioned as an advertiser analytics offering but I'd bet that's a logical next step.  Analytics for social apps certainly isn't new and the competitive landscape reminds me of the ETL lanscape back in the mid 90s.  So what sets Kontagent apart from the field?  It's the insight into who is using and spreading the apps not just how the apps are being used. IMHO the cohort and corrolation analysis create a type of influence analytics which app creators will find handy in justifing their ad rate cards. 

BI Accelerator

The BI accelerator is a recent addition to SAP BI and has shown some impressive performance gains with typical improvement factors between 10 and 100. It is based upon the TREX search engine for unstructured data applying its technology to structured data store in the InfoCubes of an SAP BI system, Figure 12.14 shows the architecture of the BI accelerator in the context of the overall SAP BW architecture. The BI accelerator replaces the MOLAP aggregate option available in previous releases of SAP BW.

Figure 12.14 BI accelerator architecture

The BI accelerator achieves these performance gains by creating special types of additional indexes — sometimes also called BI accelerator indexes — and using these indexes as the basis for massively parallel query execution. Both indexing and query execution run on a separate, highly parallel blade server.

The underlying technology is actually not new but has been part of the TREX search engine, which itself is part of the SAP NetWeaver suite. SAP BW just uses a special instance of the TREX search engine enhanced to better support searches in structured data of a business intelligence system. Creating a BI accelerator index involves three steps:

   1.  Vertical decomposition decomposes the data to be indexed by attribute (or database column) instead of by record (or table row), as it is done in traditional database indexes. This approach has been known from other search engines for non-structured data — only now applied to structured information stored in SAP BW

   2.  Smart compression involves recoding the attribute values found in the indexed data to smaller integer values using a directory, which is generated on-the-fly. Typical reductions in the size of the indexed data reach a factor of 10-20.

   3.  Horizontal partitioning divides the generated index into multiple partitions in such a way that query execution using these indexes can be run in parallel without having to share data.

BI accelerator indexes are not stored in a database, but are stored in flat files residing on the BI accelerator server. Query execution using the BI accelerator again involves up to three steps:

   1.  Load index to memory. When starting the execution of a query the system checks if the corresponding index is already (or still) available in the main memory of the BI accelerator server. If the index is not available, it is loaded into main memory. Alternatively, loading critical indexes can be triggered by external processes to ensure that these are instantly available at all times.

   2.  Aggregation. BI accelerator indexes also contain key figure values corresponding to the requested characteristic values. These key figure values are used for highly parallel on-the-fly aggregations.

   3.  Merge and return results. The final step before returning query results to the BI server is to retrieve and merge all subresults from the different parallelized query execution processes.

Using the BI accelerator has a couple of advantages over other traditional performance optimization methods. First of all, using it does not require any changes to existing information models or queries. Considerations around logical partitioning, line item dimensions or additional database indexes could even be ignored in the development of information models for use with the BI accelerator — although you should still aim for the best possible information model. As opposed to traditional aggregates, one BI accelerator index servers all queries of an InfoCube, regardless of the granularity of the result set or the actual filters used. Therefore, the manual effort for tuning aggregates is kept to an absolute minimum while the systems still provides stable, predictable query response times. Because BI accelerator indexes are not stored in a database, there’s also no need to optimize database queries or parameter sets.

On the other hand, hardware resource requirements (especially for main memory) are too demanding to allow for using the BI accelerator for all InfoCubes of the overall information model. In many applications, classic aggregates will be sufficient to provide good performance for query execution at much lower hardware requirements. Typically the BI accelerator will be deployed in scenarios with very high data volumes (hundreds of millions, or even billions of records in the fact tables), incalculable query requirements which are hard to optimize for or very high expectations (for example, with hard service level agreements) regarding average or maximum query run times. The BI accelerator does not optimize the analytic engine itself, nor does it help to cut down network transmission times. It is “only” useful to optimize database intensive query execution.

Here are a couple of my favorite sites or figuring out SEO and SEM strategies.

Compete.com

SpyFu.com

keycompete.com

While we at Circos haven't yet automated our keyword processes, keyword information services like these are used (embedded?) in our manual process.

SpyFu is my current favorite.

UPDATE - This site is also very useful for determining how your sitemap is being viewed by major search engine. It also has a handy tool for checking whether or not your site is in the Google sandbox.

Last week we launched www.circos.com at DEMO08. You can catch our 6 minute live demo here.  Stop by the site and let us know what you think. We are currently in 'preview' mode and will be adding additional content categories shortly.  Likewise if your site has a lot of user generated content or you'd like to have a more colorful search experience drop us a line.

As you may imagine we are grateful for the opportunity to launch Circos at what many consider the premier technology launch event.  We are told more than 700 companies applied for a chance to launch at this conference; we are one of 70 companies selected to present.

Stay tuned for more on information about Circos and our participation at DEMO08!

From a data-maintenance perspective, the BI accelerator is very similar to an aggregate roll-up. There is the build and fill of the index, as well as roll-ups. However, there are differences to be noted.

The build and fill of a BI Accelerator index is done manually via the data target context menu, while the roll-ups can be scheduled as process chain variants (the same exact one used for aggregates). Like aggregates, BI Accelerator indexes can be toggled active and inactive manually, and need an attribute change run scheduled after navigational attributes are changed via a master data load.

Check this out. It seams some of the more progressive BI vendors are finding applications on e-commerce sites. Endeca has teamed with Powereviews to create Buzzillions.com.  The user experience on this site is Endeca! Endeca is an interesting company although I have to say their market positioning is a bit unclear to me ("social navigation"). I thought of them as information retrieval company (think FAST, Google appliance, etc) but the more I dive in it seams they have aspirations or history in the traditional BI space. I haven't dove in enough to figure out if they are transitioning from to towards BI but my hunch is 'towards'. Google is a real threat to any company in the in the enterprise info retrieval space- including SAP. Either way, Endeca is worth a look if you have an e-commerce site.

QlikTech is on fire. They seem to be filling the white space between difficult to learn analytics tools and brain-dead dashboards. Hat tip to the founders and leaders of this company. The fact that their technology is finding applications on consumer focused websites is truly a testament to the ease of use. That said, While I have lifted the hood to check out the engine and I haven't figured out how often it needs an oil change or tune-up.

Yes, an other buzzword, TLA, skill to add the resume: Semantic Web Analytics. It occurs to me as I reread this that you may not be certain if I mean "Semantic Web" Analytics or Semantic "Web Analytics. While the former will eventually be hot IMHO the later is hot now.

Natural Language Processing (NLP) + Predictive Analytics = Marketer's Dream Come True

Analyze the footprints people leave on the web (blogs, comments, reviews), discover their preferences for the attributes of products/services they consume, and give the consumers what they want.

It's interesting to see the Web Analytics and the Marketing Analytics markets converging. It reminds me of the now old discussions regarding ERP BI tools vs the 'open' data warehouse tools. Now that the web is synonymous with marketing it isn't a big surprise to see web analytics and marketing analytics converging. Good things are bound to come of this convergence. While web analytics (IMHO) started out as interesting yet raw data that was essentially unusable. It is safe to say that today (or at least the past 5 years) it would seam most of the really interesting analytics developments have grown out of the web analytics market.  Some of the best examples of embedded data mining/predictive analytics, text mining etc etc are put to use in web applications. 

A nice book and blog to read if you find yourself getting asked more and more about web analytics is Avinash Kaushik's Web Analytics An Hour A Day. While I am a bit cautious to support the notion that 'insight' is a web analytics '2.0' deliverable the book and video (found here )of his presentation at Google earlier this month are worth the time.  That said, I'd suggest using the FF button for the first 13 mins.

Let's leave the commentary on the question in the subtitle for a separate post and focus this one on a few interesting free web analytics tools.

1- a web analytics vendor discovery tool. Enter the URL of a site and this online tool will tell you which web analytics package the site is using. Beware of false negatives - not every web analytics tool is searched for (pardon the ending of a sentence with a preposition). 

2- "WASP is the Web Analytics Solution Profiler, an extension (for Firefox) aimed at web analytics implementation specialists, web analysts and savvy web surfers who want to understand how their behavior is being analyzed." 

3-  RobotReplay and their so-called cinelytics (cinema + analytics). This session cam and playback tool is really handy but I'd check your TOS and Privacy statement before adding this java script to a commercial site. This tool sounds a lot like TeaLeaf Technologies, an SAP Labs spin out of Robert Wenig's back in 1999, but it is completely hosted and currently free. UPDATE - did I mention the servers occasionally crash? Still a promising offering.

4- Oh yeah, of course, there is Google Analytics. Arguably Google's smartest acquisition (2005).  I recently had a conversation with Paul Muret one of the founders of Urchin (now Google Analytics).  He made an interesting comment to my observation that GA was cleaning up at the bottom-end of the market and appeared to be moving up the stack into higher value areas (site map overlays, A/B, multivariate testing etc). He nodded and said (not a direct quote but you'll get the idea), yeah it's nice to be  promoting a free product when the competition is asking you to investing 100k$+ (presumably on Omniture/VisualSciences/WebTrends) and even if companies decide to use a web analytics tool from another provider, Google still benefits as those companies are more likely to invest in search engine marketing. 

(originaly posted here) 

Here are some differences between the way Germans think vs. the way Chinese think.  The design is from a Chinese national who lived in Beijing until 13 and then went off to Germany to study -  Yang Liu is her name.  She has since worked as a graphic designer in NY, Berlin, and London.  She’s won numerous awards and now has her own graphic design business.

I found this to be spot on.  Having the privilege of having had a business partner from each culture, these images resonate for me.  Check that - Morris is Taiwanese technically speaking or is it Chinese technically speaking. Hmmm?

Queuing

Head of Group

Punctuality

CLICK HERE FOR MORE IMAGES 

(originaly posted on Happenings of The Re-Employed) 

The team at Circos has been busy benchmarking Hotel Reviews and those who review them. Our research will be published during the next few weeks as a report but our initial findings are interesting enough to start sharing ahead of the report.

Background - We have developed a few software engines (among other things) that take website visitor 'footprints' and determining visitors interests as well as their influence within a community for a given area of interest. Our semantic and analytic scoring engines are currently out for a drive and have by fueled up with user generated content found on large travel review sites. We scoped the initial scoring to Hotel Reviewers and have decided to ('while we're out there') score the Hotels too.

We scoped the scoring to hotels in 5 cities and knocked out hotels that didn't meet a minimum number of reviews.  Qualifying hotels (hundreds) and reviewers (thousands) were scored across a variety of dimension to determine things like favorability, frequency, velocity, key word association, preference drivers, etc etc.  An interesting finding (other than seeing the Net Promoter Scores for the hotels and knowing who the brand advocates and detractors are) is that for hotels in San Francisco (we are still crunching number on the other cities) the greater the number of online reviews about a hotel, be that positive or negative, the higher the Net Promoter Score. Furthermore, the more reviews about a hotel the tighter the standard deviation becomes. In other words, more reviews = higher scores with less deviation between scores.

This is rather validating as we have also developed software for brands that wish to arm their advocates so these promoters may carry the brand's message throughout their electronic communications. While it is too soon to draw conclusions it may very well prove out that the risks of user generated content on a brand are out weighed by the benefits.

Check out this demo site.  Finally a demo site that is useful- that is real data, analyzed in real-time, to solve real problems. Who says pairing wine with food is hard?

Its no secret that open source, virtualization and the natural maturation in some categories is commoditizing software to a layer as burnt in as system services; it is happening fast. Very fast. It wont be long now before we see higher brain functions like analytics showing up as a standard option offered by Amazon on EC2 or in one of their partner's machine image.  Layer in Amazon S3 for storage and you have a very cheap, theoretically infinitely scalable BI solution minus the integration services and data management processes. Both of these last two items make me think there is room for a data integration/clearing hub style online service to be offered by industry - kind of like the clearing systems used by banks/credit card companies and some of the services offered by D&B and Acxiom - a service that disrupts the traditional analytics value change where each company now doesn't need to do their own ETL, if you will... but I digress....

The question raised in the subtitle of this post was relayed to me by a colleague of mine. He was pitching software to an enterprise in Asia and was faced with this preemptive price negotiation tactic.  The take away lessons were that technology, while not worthless, is not differentiator (at least not for long) and that software companies need to continue to innovate and prove they are driving value with their business partners not just acting as a utility fueling it.  If a business is a car don't be in the fueling station business be in the on-board navigation systems that provide real-time detours based on traffic conditions- business.

It's interesting to see software companies like Opsware, QlikTech, and FAST out growing the broader market in three very different categories. It seams to me these companies have something in common and it isn't necessarily a focus on higher brain functions - They execute on their plans, focus on a niche market, and attempt (in very different ways) to collapse a value chain.