923 resultados para Business -- Data processing -- Management


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Personal data about users (customers) is a key component for enterprises and large organizations. Its correct analysis and processing can produce relevant knowledge to achieve different business goals. For example, the monetisation of this data has become a valuable asset for many companies, such as Google, Facebook or Twitter, that obtain huge profits mainly from targeted advertising.

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Bibliography: p. 325-327.

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This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

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In a networked business environment the visibility requirements towards the supply operations and customer interface has become tighter. In order to meet those requirements the master data of case company is seen as an enabler. However the current state of master data and its quality are not seen good enough to meet those requirements. In this thesis the target of research was to develop a process for managing master data quality as a continuous process and find solutions to cleanse the current customer and supplier data to meet the quality requirements defined in that process. Based on the theory of Master Data Management and data cleansing, small amount of master data was analyzed and cleansed using one commercial data cleansing solution available on the market. This was conducted in cooperation with the vendor as a proof of concept. In the proof of concept the cleansing solution’s applicability to improve the quality of current master data was proved. Based on those findings and the theory of data management the recommendations and proposals for improving the quality of data were given. In the results was also discovered that the biggest reasons for poor data quality is the lack of data governance in the company, and the current master data solutions and its restrictions.

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The purpose of this study is to explore the possibilities of utilizing business intelligence (BI)systems in management control (MC). The topic of this study is explored trough four researchquestions. Firstly, what kind of management control systems (MCS) use or could use the data and information enabled by the BI system? Secondly, how the BI system is or could be utilized? Thirdly, has BI system enabled new forms of control or changed old ones? The fourth and final research question is whether the BI system supports some forms of control that the literature has not thought of, or is the BI system not used for some forms of control the literature suggests it should be used? The study is conducted as an extensive case study. Three different organizations were interviewed for the study. For the theoretical basis of the study, central theories in the field of management control are introduced. The term business intelligence is discussed in detail and the mechanisms for governance of business intelligence are presented. A literature analysis of the uses of BI for management control is introduced. The theoretical part of the study ends in the construction of a framework for business intelligence in management control. In the empirical part of the study the case organizations, their BI systems, and the ways they utilize these systems for management control are presented. The main findings of the study are that BI systems can be utilized in the fields suggested in the literature, namely in planning, cybernetic, reward, boundary, and interactive control. The systems are used both as the data or information feeders and directly as the tools. Using BI systems has also enabled entirely new forms of control in the studied organizations, most significantly in the area of interactive control. They have also changed the old control systems by making the information more readily available to the whole organization. No evidence of the BI systems being used for forms of control that the literature had not suggested was found. The systems were mostly used for cybernetic control and interactive control, whereas the support for other types of control was not as prevalent. The main contribution of the study to the existing literature is the insight provided into how BI systems, both theoretically and empirically, are used for management control. The framework for business intelligence in management control presented in the study can also be utilized in further studies about the subject.

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Felice Gigante a graduate from the New York Trade School Electronics program works on a machine in his job as Data Processing Customer Engineer for the International Business Machines Corp. Original caption reads, "Felice Gigante - Electronices, International Business Machines Corp." Black and white photograph with caption glued to reverse.

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Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

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PAMELA (Phased Array Monitoring for Enhanced Life Assessment) SHMTM System is an integrated embedded ultrasonic guided waves based system consisting of several electronic devices and one system manager controller. The data collected by all PAMELA devices in the system must be transmitted to the controller, who will be responsible for carrying out the advanced signal processing to obtain SHM maps. PAMELA devices consist of hardware based on a Virtex 5 FPGA with a PowerPC 440 running an embedded Linux distribution. Therefore, PAMELA devices, in addition to the capability of performing tests and transmitting the collected data to the controller, have the capability of perform local data processing or pre-processing (reduction, normalization, pattern recognition, feature extraction, etc.). Local data processing decreases the data traffic over the network and allows CPU load of the external computer to be reduced. Even it is possible that PAMELA devices are running autonomously performing scheduled tests, and only communicates with the controller in case of detection of structural damages or when programmed. Each PAMELA device integrates a software management application (SMA) that allows to the developer downloading his own algorithm code and adding the new data processing algorithm to the device. The development of the SMA is done in a virtual machine with an Ubuntu Linux distribution including all necessary software tools to perform the entire cycle of development. Eclipse IDE (Integrated Development Environment) is used to develop the SMA project and to write the code of each data processing algorithm. This paper presents the developed software architecture and describes the necessary steps to add new data processing algorithms to SMA in order to increase the processing capabilities of PAMELA devices.An example of basic damage index estimation using delay and sum algorithm is provided.

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"UILU-ENG 83-1724."--Cover.

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"Prepared by: Staff Development Unit, Administrative Management Section, Management Coordination Branch, Divison of Accounting Operations."