By Stefanie Rinderle-Ma, Wilfried Grossmann
This ebook offers a entire and systematic creation to remodeling process-oriented information into information regarding the underlying enterprise technique, that is crucial for every kind of decision-making. as a consequence, the authors improve step by step types and analytical instruments for acquiring high quality information based in this kind of method that complicated analytical instruments could be utilized. the most emphasis is on procedure mining and information mining thoughts and the combo of those equipment for process-oriented data.
After a common creation to the enterprise intelligence (BI) method and its constituent initiatives in bankruptcy 1, bankruptcy 2 discusses varied techniques to modeling in BI functions. bankruptcy three is an summary and offers information of knowledge provisioning, together with a piece on mammoth info. bankruptcy four tackles information description, visualization, and reporting. bankruptcy five introduces facts mining innovations for cross-sectional info. diversified options for the research of temporal information are then targeted in bankruptcy 6. as a result, bankruptcy 7 explains concepts for the research of technique information, through the creation of research concepts for a number of BI views in bankruptcy eight. The e-book closes with a precis and dialogue in bankruptcy nine. during the booklet, (mostly open resource) instruments are suggested, defined and utilized; a extra specified survey on instruments are available within the appendix, and an in depth code for the suggestions including directions on the right way to set up the software program used are available at the accompanying site. additionally, all ideas offered are illustrated and chosen examples and workouts are provided.
The booklet is appropriate for graduate scholars in machine technological know-how, and the devoted web site with examples and options makes the ebook excellent as a textbook for a primary direction in enterprise intelligence in laptop technology or company details structures. also, practitioners and business builders who're drawn to the suggestions in the back of enterprise intelligence will enjoy the transparent causes and plenty of examples.
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Extra resources for Fundamentals of Business Intelligence (Data-Centric Systems and Applications)
Example text
A number of analysis formats for the knowledge discovery process have been proposed as data mining formats. One can distinguish between academic-oriented efforts, cf. [10], and application-oriented approaches like CRISP [4], which is nowadays some kind of standard for data mining applications. Other formats are SEMMA or KDD [2]. CRISP mainly focuses on the cross-sectional view on the business process but adaptations to the state view are possible. Our definition of tasks is closely oriented towards CRISP.
Many a time, further investigations are necessary as defined by the other feedback loops. The feedback loop on the left side of Fig. 4 coming from evaluation results over a modification of analytical goal to the analytical goal initiates a new analysis cycle with a new or modified analytical goal and a new understanding of business and data. Such a new goal may be the consequence of the evaluation of the results. For example, we start with a descriptive goal and learn from the analysis results that the analysis of a predictive model may be reasonable, leading to a respective modification of the analytical goal.
Note that the goal orientation is complementary to the life-cycle analysis of the business process along three phases: design time, run-time, and change time. At design time, the business process is described in terms of process models (cf. Sect. 2) defined in agreement with a KPI for certain business needs. Many a time, the background for the design is formulated as a business plan, and detailed formulation requires the investigation of different analytical goals. For example, if we are interested in launching a new product, analytical goals like prediction of market opportunities or detailed product description have to be achieved.