Question1 Quantitative data are measures of values or counts and are expressed as numbers (www.abs.gov.au). In other words‚ quantitative data are data about numeric variables (www.abs.gov.au). Four types of quantitative data are interval‚ nominal‚ ordinal and ratio. Firstly‚ interval scales are numeric scales in which we know not only the order‚ but also the exact differences between the values (www.mymarketresearchmethods.com). Other than that‚ interval data also sometimes called integer is measured
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Qualitative data analysis What Is Qualitative Analysis? Qualitative modes of data analysis provide ways of discerning‚ examining‚ comparing and contrasting‚ and interpreting meaningful patterns or themes. The varieties of approaches - including ethnography‚ narrative analysis‚ discourse analysis‚ and textual analysis - correspond to different types of data‚ disciplinary traditions‚ objectives‚ and philosophical orientations. What Is Qualitative Analysis? We have few agreed-on canons for qualitative
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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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Electronic Data Interchange * Electronic data interchange (EDI) is the structured transmission of data between organizations by electronic means‚ which is used to transfer electronic documents or business data from one computer system to another computer system‚ i.e. from one trading partner to another trading partner without human intervention. It is more than mere e-mail; for instance‚ organizations might replace bills of lading and even cheques with appropriate EDI messages. It also refers
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Financial Services Data Management: Big Data Technology in Financial Services Big Data Technology in Financial Services Introduction: Big Data in Financial Services ....................................... 1 What is Driving Big Data Technology Adoption in Financial Services?3 Customer Insight ........................................................................... 3 Regulatory Environment ................................................................ 3 Explosive Data Growth ....
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Introduction Data management within Human Resources (HR) is essential as this can be used when organisations have to make decisions‚ contact employees and also satisfy legal requirements. Aims and Objectives The aim of this report is to show the importance of why organisations must collect HR data. The objectives are: * To identify two types of data organisations must collect and how this supports HR * To describe two methods of storing HR records and the benefits of each * To explain two
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READING QUESTIONS DAY ANSWERS 1. Which of the following reading components do you find the easiest and the most difficult? Vocabulary Sentence/Syntax Getting the main idea Comprehension Others:_______________ Easiest: _____________ Difficult: _______________ EASIEST COMPONENTS: Vocabulary - 3 Sentence/Syntax - 11 Getting the main idea - 16 Comprehension - 1 DIFFICULT COMPONENTS: Vocabulary - 5 Sentence/Syntax - 9 Getting the main idea - 5 Comprehension – 11 2. Why do you
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Presentation Status Update For the America and the World Presentation‚ our team has focused on dividing into sections to work individually. Each group member is responsible for providing APA formatted slides‚ efficient research‚ and credible sources to prepare their portion of the presentation. Jesse will be the team leader and format the presentation to ensure that we attain our goal of a powerful presentation that offers consistency throughout and a theme for which we
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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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5.3.3 Data cleaning Data cleaning helps to remove all unnecessary data. Data cleaning attempts to fill in missing values‚ smooth out noise while identifying outliers and correct inconsistencies in the data. Data cleaning is usually an iterative two-step process consisting of discrepancy detection and data transformation. 5.3.4 Data analysis Data analysis is also known as analysis of data or data analytics‚ is a process of inspecting‚ cleansing‚ transforming and modeling data with the goal of discovering
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