Analytics is the scientific process of finding and sharing patterns within data.<\/p>\n

Key Takeaways<\/span><\/h2>\n
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Analytics finds patterns in data to help make better decisions in areas like business, healthcare, and science.<\/li>\n
Important steps in analytics history include the creation of bar charts, the tabulating machine, SQL, and data warehouses.<\/li>\n
The four types of analytics \u2013 descriptive, diagnostic, predictive, and prescriptive \u2013 help us define analytics as a way to understand past trends and guide future strategies.<\/li>\n
Tools like data aggregation, data mining, big data analysis, text mining, and simulation reveal valuable insights.<\/li>\n
Analytics is used in website tracking, fraud detection, CRM, risk analysis, and targeted marketing, among others.<\/li>\n<\/ul>\n<\/div><\/div>\n
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\n What is Analytics?<\/a>\n <\/div>\n <\/li>\n
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\n Key Takeaways<\/a>\n <\/div>\n <\/li>\n
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\n History of Analytics<\/a>\n <\/div>\n <\/li>\n
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\n How Analytics Works<\/a>\n <\/div>\n <\/li>\n
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\n Types of Analytics<\/a>\n <\/div>\n <\/li>\n
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\n Common Components of Business Analytics<\/a>\n <\/div>\n <\/li>\n
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\n Analytics Examples<\/a>\n <\/div>\n <\/li>\n
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\n Analytics Pros and Cons<\/a>\n <\/div>\n <\/li>\n
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\n The Bottom Line<\/a>\n <\/div>\n <\/li>\n
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\n FAQs<\/a>\n <\/div>\n <\/li>\n <\/ol>\n
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