Business processes don’t execute only at the application layer. Just as thought processes aren’t entirely divorced from the synaptic firings of the underlying neurons.
Most business activity monitoring (BAM) tools I’ve come across only operate at the business level. In other words, they are geared to monitoring, tracking, correlating, visualizing, and analyzing those metrics that come from business process management (BPM) platforms, enterprise resource planning (ERP), and other application platforms. That’s essential, but it’s only half the battle of process optimization. To deliver the promised service levels, BAM dashboards should integrate closely with business service management (BSM) dashboards, thereby mapping application services to the underlying server, storage, network, and other infrastructure components. In this way, IT can provide full-stack visibility, provisioning, and control over every component that affects every step of every business process. If you need a deep drilldown on BSM, check out the excellent research by my colleague Peter O’Neill, who specializes in this area.
It was my pleasure to participate in the latest DM Radio podcast panel yesterday. Eric Kavanaugh and Jim Ericson always do a fine job of organizing these events, and, with their stellar industry panels and fun “morning drive-time crew” on-air patter, they keep it lively. And these guys actually know a thing or two about information management.
The latest DM Radio panel was right in my core coverage area. They called it their “Third Annual Appliance Showdown.” That got to me to thinking: early 2008 (when they held their first) was also when Forrester began our coverage of data warehousing (DW) appliances, starting with publication of my report “Appliance Power: Crunching Data Warehousing Workloads Faster And Cheaper Than Ever.” When I published that report, DW appliances were still not quite in the enterprise mainstream, because they were still regarded by enterprise IT as, in the words of Kavanaugh, an “adjunct” to the enterprise DW (EDW) for fast table scans and query processing, rather than as platform that could scale to support all EDW functions.
Our latest featured podcast is Jim Kobielus' "The New Decade Of Advanced Analytics: Roll Over Rocket Scientists!".
In this podcast, BP&A Senior Analyst Jim Kobielus discusses the increasing adoption of more user-friendly data mining tools. This trend, he argues, is helping advanced analytics become a core feature of operational business intelligence (BI) suites.
Decisions are a very human investment of attention to a problem, and gut feel--the stream of intuition, impulse, memory, and emotion behind all behavior--is the impetus driving every decision that people make
Here now is the broader conceptual model that I promised in the prior blog post. As I said, I built conceptual hooks in my decision support ROI model to address broader requirements for decision automation and decision management.
In his latest podcast, Jim discusses the increasing adoption of more user-friendly data mining tools. This trend, he argues, is helping advanced analytics become a core feature of operational business intelligence (BI) suites.
I’m developing a return on investment (ROI) calculator for data warehousing (DW) appliances, using the Forrester Total Economic Impact methodology.
At the heart of that is a conceptual ROI model that can be applied to any decision support infrastructure, not just DW appliances (though indeed high-quality decision support is the raison d’etre for DW appliances).
That said, and not wanting to bog down forthcoming syndicated TEI study with a lot of this conceptual material, here are the core principles of this conceptual model , plus a discussion of how, net-net, they map to the key benefits of a DW appliance:
You never know what’s coming at you next, which is why process agility is so important. Your organization must have a ready response for anything. And you must make sure that every process participant can identify, at their level, what that response might be, so they can take appropriate action.
I recently came across a trade-press article with the headline “Mining the Cloud.” The cynic in me immediately issued a silent scoff: How is that different from “crawling the Web”? Are we just mapping old wine to shinier new bottles? Or is there something different here?
But, seeing as how I too like to proliferate discussions of mining this or that information type, I was willing to cut the reporter some slack. The article was from Redmond Developer, and concerns “Project Dallas” under Microsoft’s Azure cloud initiative. Essentially, “Project Dallas” (still in beta) supports discovery, manipulation, visualization, and analysis of data retrieved from multiple public, commercial, and private data sources via the Azure cloud. “Dallas” allows enterprises to provide users (via REST, Excel PowerPivot, and/or Visual Basic applications) with online access to aggregated feeds via Azure, which essentially operates as an online information marketplace. Also, “Dallas” allows customers to have Azure host their data for them, or simply continue to host it on their own premises while the cloud service connects securely to it.