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CHAPTER 3 Data Analysis In this chapter, there is a flow that can be used to analyze the characteristics of a large amount of data collection. We offer basic plots (bar graphs, line graphs, and pie charts), graphs (boxplots and histograms), and various enhancements that extend the ability of these plots to display more information. We focus on how images and different tasks can support data mining tasks, from supervised tasks (time series prediction, classification, and forecasting) to unsupervised tasks. , and provides some guidance on specific images to use for each data mining task. We also explain the benefits of interactive visualization over static plots. The chapter concludes by presenting specific strategies suitable for data with specific structures (level, network and geographic). 3.1 Benefits of Data Visualization1 The popular saying “a picture is worth a thousand words” refers to the ability to synthesize vast amounts of information into a coherent and easy-to-understand graphical representation. When it comes to numbers, data visualization and number summaries provide powerful tools for exploring data and effective ways to present results. Where do visualization techniques fit into the data mining process, as described so far? It is mainly used in the processing part of the data mining process. Visualization supports data cleaning by finding false values (eg, death…
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Do you want to help your friend? Do you need an additional source of income? Apply to be a tutor there! Top teachers earn over $7,500 per month! Effective business decision-making depends on quality information. This is a reality in today’s competitive business environment that requires quick access to data warehouses, organized in ways that improve business performance, and provide fast, accurate and relevant information. that’s it. BI architectures emerged to meet these requirements, with data warehousing at the core of this process.
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In this article, we will explain the definitions, relationships, and differences between data warehouse and business intelligence, and provide a BI architecture diagram that will explain the relationship between these terms and the systems involved. him. But first, let’s start with a basic definition.
What is BI Architecture? Business intelligence architecture is a term used to define standards and policies for data management with the help of computer-based techniques and technologies that create business intelligence systems used in online data visualization, reporting and analysis. One component of BI architecture is data warehousing. The processing, storage, cleaning and extraction of data must be done by a central storage system, that is, a data warehouse, which is considered a key component of business intelligence. But what about communication? What is Data Warehousing and Business Intelligence? Data warehousing and business intelligence are terms used to describe the process of storing all of the company’s data in internal or external databases from various sources with ‘the focus on analysis and the generation of actionable insights through online BI tools. One without the other is impossible, and now we will explain the basics of the system world through the BI architecture diagram.
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