report will give an overview of the aim behind collecting data‚ types of data collected‚ methods used and how the collection of the data supports the department’s practices. It will also give a brief outlook on the importance of legislation in recording‚ storing and accessing data. Why Organisations Need to Collect Data * To satisfy legal requirement: every few months there is some request from the government sector to gather‚ maintain and reports lots of information back to them on how many
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Analyzing Data IT206 September 2‚ 2011 Don Shultz Analyzing Data The five basic steps that are required for analyzing data using Microsoft Access according to the article by Samuels and Wood (2007. The steps are to gather the data‚ create a database‚ edit and validate data‚ connect data files‚ and perform queries. The first step is to determine exactly what analyzes you want to perform and ensure that you gather all that is needed. Keep in mind to import into Access it has to be formatted
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Factors that influence the selection of data collection instruments Data Collection is an important aspect of any type of research study. Inaccurate data collection can impact the results of a study and ultimately lead to invalid results. Data collection methods for impact evaluation vary along a continuum. At the one end of this continuum are quantitative methods and at the other end of the continuum are Qualitative methods for data collection. A data collection instrument is a tool for monitoring
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The Evolution of Data Models The quest for better data management has led to different models that attempt to resolve the file system’s critical shortcomings. Because each data model evolved from its predecessors‚ it is essential to examine the major data models in roughly chronological order. 1.1 The Hierarchical Model A Hierarchical Database Model is a data model in which the data is organized into a tree-like structure. The structure allows representing information using parent/child relationships:
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Transforming Logical Data Models into Physical Data Models Susan Dash Ralph Reilly IT610-1404A-01 According to an article written by Tom Haughey the process for transforming a logical data model into a physical data model is: The business authorization to proceed is received. Business requirements are gathered and represented in a logical data model which will completely represent the business data requirements and will be non-redundant. The logical model is then transformed into a first cut physical
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to confidentiality. They are: • Data protection act 1998 • Access to personal files act 1987 • Access to medical records act 1990 The following have to follow legislation mentioned above: • Nurseries-private/government based/child minders/nannies • Hospitals-private/government funded • Schools-private/government funded • Doctor surgeries • Care homes • NHS Data protection act 1998 The Data protection act was developed to give
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Differentiating Between Market Structures on Kudler Fine Foods ECO/365 University of Phoenix Week 4 Individual Assignment March 11‚ 2013 Differentiating Between Market Structures The analysis will apply important microeconomic concepts toward the competitive strategies of the Kudler Fine Food Virtual Organization‚ which affect its long-term profitability. The analysis will evaluate the differences between market structures and review the organization’s strategic plan‚ marketing overview
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mmTASK 1 a) Explain the following types of data communication networks and their applications * Public switched telephone network (PSTN) * Local area networks (LANs) * Metropolitan area networks (MANs) * Wide area networks (WANs) * Packet switched data network (PSDN)‚ * Integrated services digital network (ISDN) Public switched telephone network (PSTN) Public Switched telephone network (PSTN) is the global collection of interconnects originally designed to
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Data Warehousing Failures Eight studies of data warehousing failures are presented. They were written based on interviews with people who were associated with the projects. The extent of the failure varies with the organization‚ but in all cases‚ the project was at least a disappointment. Read the cases and prepare a one or two page discussion of the following: 1. What’s the scope of what can be considered a data warehousing failure? Discuss. 2. What generalizations apply across
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A MULTIDIMENSIONAL DATA MODEL Data warehouses and OLAP tools are based on a multidimensional data model. This model views data in the form of a data cube. FROM TABLES TO DATA CUBES What is a data cube? A data cube allows data to be modeled and viewed in multiple dimensions. It is defined by dimensions and facts. In general terms‚ dimensions are the perspectives or entities with respect to which an organization wants to keep records. Each dimension may have a table associated with it‚ called
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