The problems come when vendors obscure the differences between data and application integration to broaden the appeal of their tools. You'll find EAI and messaging vendors tout their tools for DI, and ETL vendors talk about operational DI.

When evaluating tools, it's important that you realize that data integration and application integration are not the same thing.

The lawsuit is based on a 1998 patent (6,195,662) fpr ETL:

While not a stated theme, I noticed an increase in Web data as the subject of analysis, or married to internal transactional and customer data. There was even a session on analyzing social networks based on cellular call data — not exactly Web, yet a topic most commonly associated with Web businesses. There were presentations by eBay, PayPal, and Netflix as well as non-Web companies and government departments.

When you look at data usage, there are two types of large data problems. The classic DW model involves analyzing subsets of the total data, and occasionally scanning all the data. The other model is the need to analyze very large data sets that would normally be impractical, like looking at a year of web traffic or call details.

What's notable about this is that we aren't talking about just BI tools. This combination of vendors provides complete coverage of the standard data warehouse technology stack, from platform to BI. If you wanted to, you could acquire a complete open source BI solution at this event.

DatAllegro has been secretive over the past few years about its customer base, leading some analysts (including me) to wonder how well they're doing in the highly competitive data warehouse platform and appliance market. They have only three customers that I know of, but they say that the largest of these sites are storing hundreds of terabytes. This offers a compelling scalability story for Microsoft once the DatAllegro technology is merged into SQLserver.

Ideologies exist to simplify the world by trying to separate everything into two buckets: good and evil. A spreadsheet being used for BI, like the devil, is the embodiment of badness. As with all good demons, a spreadsheet entices people to make bad choices and do bad things like retaining data in files on their PCs.

How does it entice people? By offering something of value, like simplicity or ease of use. Ever try to add a quick formula to a Web-delivered report? It can be a nightmare. Export the report into Excel and it’s a snap. A spreadsheet is malleable, unlike the rigid offerings of the BI orthodoxy.

"Doesn't DW-in-the-cloud suffer from the same fundamental problem as DW-as-a-Service in that you have to pump all of your proprietary, strategic, highly sensitive data outside of the firewall onto someone else's hardware?"

I think that's a valid argument, provided your company has no external network connectivity. If you have an external connection, then all bets are off. It's worth looking at some networking pre-history to see why this has been true for decades.

"EMC and ParAccel have jointly engineered and developed a highly scalable and performant analytic appliance. This solution is built on EMC CLARiiON midrange CX-3 UltraScale networked storage and ParAccel's analytic columnar data store. Customers can deploy the EMC/ParAccel analytic appliance by simply extending their existing EMC footprint on enterprise ready storage while leveraging EMC's proven solutions."

There's definitely going to be cost-cutting after the deal is done. There are some specific quotes from Microsoft's offer worth highlighting.

The fact that a little startup like ParAccel can enter the market with a database to support business intelligence that beats the TPC-H results of all the major vendors on both performance and price should wake people up. Particularly when the performance increase is so large while significantly decreasing cost.

As a software vendor, IBM is all about enterprise infrastructure. BI as it's talked about today is mostly reporting infrastructure, and as such has become mainstream infrastructure — exactly the sort of thing IBM does.

This is a great thing for SAP since they can now start taking in sales for BI where once it all went to third parties. They also get a decent set of data integration and data quality products to complement SAP's sore applications. It's good for Business Objects too, since this opens up the market for all those SAP accounts.

Not that long ago, you would look at listings in your price range and try to work out where they were and whether they were in nice neighborhoods. More likely, a real estate agent would do this for you. Their value was almost entirely access to information and knowing how to get at it via the multi-list service.

Speaking at the recent TDWI Executive Summit, I talked about Web mashups, BI and the blurring between the two. One of the mashups I showed was ColorPickr, a nifty app that pulls images from photo site Flickr based on your choice of color from a palette.

Predictive Analytics still hot — Predictive analytics (a.k.a. data mining) seems to be the topic most people are interested in hearing about. A lot of the engineering problems we faced with data mining in the '90s have been solved and cheap computing power makes broader use more feasible. The catch is that it still takes expertise to understand which techniques work best for different problems. Expect a new subclass of BI professionals who know PA tools and techniques, just as we have BI tool and design experts now.

Lots of people talking about data governance — There seem to be two threads driving this: