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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Data Cleansing/Scrubbing The concept of information cleansing / scrubbing is to improve the quality of organizational information and thus the effectiveness of decision making businesses must formulate a strategy to keep information clean. This is a process that weeds out and fixes or discards inconsistent‚ incorrect‚ or incomplete information. Specialized software tools use sophisticated algorithms to parse‚ standardize‚ correct‚ match and consolidate data warehouse information. This is vitally
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What is a data warehouse and why is REI building one? A data warehouse can be described as a “database that stores current and historical data of potential interest to decision makers throughout a company. The data originate in many core operational transaction systems‚ such as systems for sales‚ customer accounts‚ and manufacturing‚ and may include data from Web site transactions.1” REI is building a data warehouse to improve the company and to meet the needs of the customers. REI’s data warehouse
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Data transmission methods Transmission Transmission is the act of transporting information from one location to another via a signal. The signal may be analog or digital‚ and may travel in different media. Transmission: Communication of data by propagation and processing of signals. Signal processing is the representation‚ transformation and manipulation of signals plus the information they contain. Signal Types Signals: An electric or electromagnetic representations of data by which data is
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Importance of good quality data and DATA ANALYSIS for Research Methods INTRODUCTION Conducting a survey is often a useful way of finding something out‚ especially when `human factors ’ are under investigation. Although surveys often investigate subjective issues‚ a well-designed survey should produce quantitative‚ rather than qualitative‚ results. That is‚ the results should be expressed numerically‚ and be capable of rigorous analysis. The data obtained from a study may or
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CHAPTER 3 DATABASES AND DATA WAREHOUSES Building Business Intelligence CONTACT INFORMATION: Stephen Haag is the primary author of this chapter. If you have any questions or comments‚ please direct them to him at shaag@du.edu. THIS CHAPTER/MODULE IN SHORT FORM… This chapter introduces your students to the vitally important role of information in an organization and the various technology tools (databases‚ DBMSs‚ data warehouses‚ and data-mining tools) that facilitate the management
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contains only three base cells: (1) (a1‚ b2‚ c3‚ d4; ...‚ d9‚ d10)‚ (2) (a1‚ c2‚ b3‚ d4‚ ...‚ d9‚ d10)‚ and (3) (b1‚ c2‚ b3‚ d4‚ ...‚ d9‚ d10)‚ where a_i != b_i‚ b_i != c_i‚ etc. The measure of the cube is count. 1‚ How many nonempty cuboids will a full data cube contain? Answer: 210 = 1024 2‚ How many nonempty aggregate (i.e.‚ non-base) cells will a full cube contain? Answer: There will be 3 ∗ 210 − 6 ∗ 27 − 3 = 2301 nonempty aggregate cells in the full cube. The number of cells overlapping twice is 27
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Dealing with Data: Using NVivo in the Qualitative Data Analysis Process The decision to use computer software programs for qualitative data analysis is essentially up to the person analyzing the data. There are positives and negatives when using these software programs to analyze data. A researcher in London wanted to find out if using the software package NVivo would be helpful in her data analysis process. The purpose of the study was to consider the difficulties surrounding interrogation
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PASS/REFER COMMENTS LO1: Understand what data needs to be collected to support HR practices 1.1 Explain why an organisation needs to Good explanation as to why organisations Pass collect and record HR data. need to collect and record HR data. 1.2 Identify the range of HR data that Clear identification of the type of data that organisations collect and how this Pass organisations collect which support HR supports HR practice. practice. LO2: Know how HR data should be recorded and stored 2.1 Describe
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1 Thomas H. Davenport‚ Paul Barth and Randy Bean How ‘Big Data’ Is Different Please note that gray areas reflect artwork that has been intentionally removed. The substantive content of the article appears as originally published. REPRINT NUMBER 54104 W I N N I N G W I T H D AT A : E S S AY How ‘Big Data’ Is Different These days‚ lots of people in business are talking about “big data.” But how do the potential insights from big data differ from what managers generate from traditional analytics
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