Stateful means the computer or program keeps track of the state of interaction, usually by setting values in a storage field designated for that purpose. Stateless means there is no record of previous interactions and each interaction request has to be handled based entirely on information that comes with it.
Unlike traditional BI, an operational BI system should be focused on influencing the interaction with your customer to provide benefit to both the customer and your business. Traditional BI, while often seen as a tool with a very fuzzy ROI, is nonetheless necessary for conducting business. Operational BI, on the other hand, provides a much clearer benefit because it directly addresses your business.
The power of Decision Management in this kind of scenario is threefold.
Firstly it focuses on the decisions themselves - what decisions matter to the customer interaction. This ensures that the data being collected and used is that which will make a difference. Beginning with the decision in mind in this way focuses analytics and data gathering.
Secondly it allows the decision to be made consistently across channels so that customers get the same service from the agent at the gate, the call center, the service center or the kiosk. Operational BI assumes there is a person to make the decision and so cannot deliver this true cross-channel consistency.
Thirdly, Decision Management recognizes that policies and regulations matter as much, sometimes more, than data. Presenting the data and even its analysis to someone who then fails to follow procedure is not helpful. Decision Management combines the policy aspects of a decision with the analytic aspects in a way Operational BI does not.
In 2009, Web analytics managers have a multitude of different tools to select to deploy at their corporation. Sets of tools from industry leaders, such as Omniture, WebTrends, Unica, CoreMetrics , Google, and Yahoo, are among the most popular, while options from smaller players like ClickTracks and Woopra exist as well. In theory, you deploy a tool, customize it to fit your needs, and start analyzing the reports — and it all goes swimmingly, right?
Then why have many corporations already chewed through two, maybe even three tools over the last several years, or deployed multiple tools in an attempt to arrive at where they need to be — delivering comprehensive and systematic analysis to their business community, helping to drive action from insight and taking the mantra of “competing on analytics” and “data driven culture” to the next level? Several factors cause disconnects between the promise of a tool and the successful use of a tool, which cause a tool to fail:
The book is out: Yahoo! Web Analytics: Tracking, Reporting, and Analyzing for Data-Driven Insights.
His philosophy is that you should focus on three different but equally important tasks; A) Collecting Data, B) Reporting on Data and C) Deriving insight from Data. Dependant ones vantage point, one or more of the chapters will be in focus. He has divided the book into three parts to reflect these broad tasks.
Part 1, “Advanced Web Analytics Installation,” consists of Chapters 1 through 5. The focus is on data collection. True competitive advantage in web marketing comes from collecting the right data, but also, and no less important, from configuring your web analytics tool in such a way that you can derive insight from the data. Part 1 features detailed code examples that webmasters or developers can apply directly. Marketing people and executives will learn the opportunities they can demand from this tool. He also shows you how to add reporting dimensions to the predefined report structures for fantastic filtering and segmentation opportunities.
Part 2, “Utilizing an Enterprise Web Analytics Platform,” encompasses Chapters 6 through 10, where he focuses on reports. Creating reports is an easy feat, but remember that reports are never better than the data you collect. You need an exceedingly good understanding of how to work with your data. Part 2 is less technical than the first part. In it he teaches you to use your reporting toolbox to provide targeted answers to specific questions, such as “How much revenue did we make from first-time organic search visitors from Canada last week?” For this and many other questions you’ll encounter there is no standard report, but you will know how to get this answer and hundreds of others when you’re through with this section.
Part 3, “Actionable Insights,” encompasses Chapters 11 through 13 and focuses on how to take action on your data to optimize your web property. Having gone through the effort of implementing the data collection and reporting strategies in Parts 1 and 2, you will have gained enough insight to start an optimization process. Part 3 introduces you to optimization using a set of actionable insights. This is merely an appetizer, and the handful of optimizations he presents are not, by any means, the only ones you can pursue. But the ideas and attitude behind them can most definitely be copied and carry you down other optimization avenues. Think of this section as an idea catalog. One of the most important questions he tackles in this section is paid search optimization.
The Zachman Framework is a framework for enterprise architecture, which provides a formal and highly structured way of viewing and defining an enterprise.
The Framework in practice is used for organizing enterprise architectural "artifacts" in a way that takes into account both:
who the artifact targets for example, business owner and builder, and
what particular issue for example, data and functionality is being addressed.
These artifacts may include design documents, specifications, and models.[3]
The Framework is in essence a matrix,[4]. It is named after its creator John Zachman, who first developed the concept in the 1980s at IBM. It has been updated several times ever since.[5]
Das Zachman Framework ist ein 1987 von John Zachman konzipierter domänenneutraler Ordnungsrahmen zur Entwicklung von Informationssystemen.
Es bildet dabei einen Leitfaden, der Vorschläge enthält, welche Aspekte aus welchen Perspektiven Berücksichtigung finden sollten, um die IT-Architektur einer Unternehmung erfolgreich aufzustellen. Mit Hilfe dieser Modellierung kann sowohl die Dokumentation- als auch die Planung eines solchen Projekts unterstützt werden, wenn bspw. nachvollzogen werden soll, welche Entscheidungen welche technischen Umsetzungen nach sich gezogen haben.
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E. Mohyeldin, M. Fahrmair, W. Sitou, and B. Spanfelner. The 16th Annual IEEE International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC05), 11-14 September 2005, Berlin, Germany, (2005)
M. LeMay, R. Nelli, G. Gross, and C. Gunter. HICSS '08: Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences, page 174. Washington, DC, USA, IEEE Computer Society, (2008)
T. Bucher, R. Fischer, S. Kurpjuweit, and R. Winter. Enterprise Distributed Object Computing Conference Workshops, 2006. EDOCW '06. 10th IEEE International, (October 2006)