Big Data‚ Data Mining and Business Intelligence Techniques 2 What is Data? • Data is information in a form suitable for use with a computer. • There are two types of data ▫ Structured ▫ Unstructured • The total volume of data is growing 59% every year. • The number of files grow at 88% every year. 3 What is Big Data? Exa Analytics on Big Data at Rest Up to 10‚000 Times larger Peta Data Scale Giga Data at Rest Tera Data Scale Mega Traditional Data Warehouse
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assumptions are made based on judgment Methodologies This case study analysis is based on secondary data. The data analysis was conducted using following procedure: * Qualitative Analysis Industry analysis is conducted through porter’s five forces model and company analysis through SWOT analysis‚ country risk analysis through ICRG model. * Quantitative analysis The data are analyzed using simple tools like ratio analysis‚ free cash flow to firm
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Data Anomalies Normalization is the process of splitting relations into well-structured relations that allow users to inset‚ delete‚ and update tuples without introducing database inconsistencies. Without normalization many problems can occur when trying to load an integrated conceptual model into the DBMS. These problems arise from relations that are generated directly from user views are called anomalies. There are three types of anomalies: update‚ deletion and insertion anomalies. An update anomaly
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Big Data which companies are easily able to collect from their businesses‚ customers and employees. It explains the numerous advantages of using the data collected by companies effectively so that it can be used by the company in improving its efficiencies‚ sales‚ faster and quicker turnaround which in turn would lead to increase revenues and finally increased profits (which is what the stakeholders of the company are looking for).It illustrates the prominent fact that companies that are data-driven
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Module 815 Data Structures Using C M. Campbell © 1993 Deakin University Module 815 Data Structures Using C Aim After working through this module you should be able to create and use new and complex data types within C programs. Learning objectives After working through this module you should be able to: 1. Manipulate character strings in C programs. 2. Declare and manipulate single and multi-dimensional arrays of the C data types. 3. Create‚ manipulate and manage C pointers
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Data Gathering ➢ used to discover business information details to define the information structure ➢ helps to establish the priorities of the information needs ➢ further leads to opportunities to highlight key issues which may cross functional boundaries or may touch on policies or the organization itself ➢ highlighting systems or enhancements that can quickly satisfy cross-functional information needs ➢ a complicated task especially in a large and complex system ➢ must
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Data Mining: What is Data Mining? Overview Generally‚ data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue‚ cuts costs‚ or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles‚ categorize it‚ and summarize the relationships identified
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technique used to expedite the investigation of system requirements. ____ 16. A physical model shows what the system is required to do in great detail‚ without committing to any one technology. ____ 17. The modern structured analysis technique uses data flow diagrams (DFDs) and entity-relationship diagrams (ERDs). ____ 18. One of the
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Education Matters One of the proudest moments of life is walking across the stage receiving a high school diploma. However‚ approximately 1.2 million high school students fail to graduate each year. Three out of 10 tenth-grade students in American schools do not graduate. About 20 percent of the drop-outs are white or Asian while 45 percent are blacks and Hispanics (Gales). One of the biggest debates regarding the mandatory dropout age is deciding whether it should be raised or kept the same.
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Collecting Data Shauntia Dismukes BSHS/405 June 1‚ 2015 Tim Duncan Collecting Data Data collection is the process of gathering and measuring information on variables of interest‚ in an established systematic fashion that enables one to answer stated research questions‚ test hypotheses‚ and evaluate outcomes. In this paper I will define the importance of data collecting in the helping field. While working in the helping field‚ there are many important things that must happen
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