Operational Data Systems
There are several systems and technologies commonly used to manage operational data. These tools accessible for data management are referred to as Clinical Data Management Systems (CDMS). The commonly used tools include: CLINTRIAL, ORACLE CLINICAL, RAVE, MACRO and also eClinical Suite (Krishnankutty et al., 2012). With regard to functionality, these software technologies are relatively comparable and there is no substantial lead of one system set against the other. These software technologies are costly and require sophisticated Information Technology infrastructure to function (Krishnankutty et al., 2012). However, other personalized systems and technologies commonly used to manage operational data include: OpenClinica, openCDMS, TrialDB, and PhOSCo. These data management software technologies are free with regards to cost and comparatively effective against their viable equivalents (Krishnankutty et al., 2012).
In this method, the systems and technology employed in this discussion is OpenClinica. To begin with, OpenClinica is a software platform that is web-based. This system was technologically established and advanced by Akaza Research, which manages clinical research studies for several different sites. In particular, OpenClinica enables protocol alignment, designing of case report forms, electronic data capture (EDC), recovery, and data management (Ashwin, 2006). This technology takes...
Data Warehouse and Business Intelligence In order to write a paper on the similarities and contrast between data warehouse and business intelligence, we need to first define each term before finding the similarities and contrasts between the two. Data Warehouses Data warehouse are used for storing data for archival, analysis, and security purposes. The warehouses themselves are made up of one or many computers (i.e. servers) that are connected together into one giant
Data Warehousing: A Strategic Weapon of an Organization. Within Chapter One, an introduction to the study will be provided. Initially, the overall aims of the research proposal will be discussed. This will be followed by a presentation of the overall objectives of the study will be delineated. After this, the significance of the research will be discussed, including a justification and rationale for the investigation. The aims of the study are to
The use of databases as the system of record is a common step across all data mining definitions and is critically important in creating a standardized set of query commands and data models for use. To the extent a system of record in a data mining application is stable and scalable is the extent to which a data mining application will be able to deliver the critical relationship data,
Growth Aided by Data Warehousing Adaptability of data warehousing to changes Using existing data effectively can lead to growth Uses of data warehouses for Public Service Getting investment through data warehouse Using Data Warehouse for Business Information Ongoing changes in Data Warehousing The Origin of Data Warehousing and its current importance Relationship between new operating system and data warehousing Developing Organizations through Data Warehousing Telephone and Data Warehousing Choose your own partner Data Warehousing for Societal Causes Updating inaccessible data Data warehousing for investors Usefulness
Effective Communication in the Workplace "Workplace communication" is information transmission between two people or two groups within a company. It may be in the form of text messages, emails, notes, voicemails, and so forth. Effective communication is truly essential as organizations cannot thrive, and might even end up collapsing, without it. Expecting all employees to develop excellent communication skills is an unrealistic goal, However, several tactics exist to improve external and
The tools used, in this case, for knowledge discovery and data mining where based on artificial neural networks (ANN) and consisted of four different models. All models represented supervised learning models with a known output. The four models of the ANN were dynamic network, prune network, the multilayer perceptron, and the radial basis function network. The main challenge for its implementation was that data needed to be cleaned so the data
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